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Zhou X, Zhang Z, Du H, Qiu B. MLMFNet: A multi-level modality fusion network for multi-modal accelerated MRI reconstruction. Magn Reson Imaging 2024; 111:246-255. [PMID: 38663831 DOI: 10.1016/j.mri.2024.04.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/09/2024] [Accepted: 04/19/2024] [Indexed: 06/01/2024]
Abstract
Magnetic resonance imaging produces detailed anatomical and physiological images of the human body that can be used in the clinical diagnosis and treatment of diseases. However, MRI suffers its comparatively longer acquisition time than other imaging methods and is thus vulnerable to motion artifacts, which ultimately lead to likely failed or even wrong diagnosis. In order to perform faster reconstruction, deep learning-based methods along with traditional strategies such as parallel imaging and compressed sensing come into play in recent years in this field. Meanwhile, in order to better analyze the diseases, it is also often necessary to acquire images in the same region of interest under different modalities, which yield images with different contrast levels. However, most of these aforementioned methods tend to use single-modal images for reconstruction, neglecting the correlation and redundancy information embedded in MR images acquired with different modalities. While there are works on multi-modal reconstruction, the information is yet to be efficiently explored. In this paper, we propose an end-to-end neural network called MLMFNet, which helps the reconstruction of the target modality by using information from the auxiliary modality across feature channels and layers. Specifically, this is highlighted by three components: (I) An encoder based on UNet with a single-stream strategy that fuses auxiliary and target modalities; (II) a decoder that tends to multi-level features from all layers of the encoder, and (III) a channel attention module. Quantitative and qualitative analyses are performed on a public brain dataset and knee brain dataset, which show that the proposed method achieves satisfying results in MRI reconstruction within the multi-modal context, and also demonstrate its effectiveness and potential to be used in clinical practice.
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Affiliation(s)
- Xiuyun Zhou
- Biomedical Engineering Center, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Zhenxi Zhang
- Biomedical Engineering Center, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Hongwei Du
- Biomedical Engineering Center, University of Science and Technology of China, Hefei, Anhui 230026, China.
| | - Bensheng Qiu
- Biomedical Engineering Center, University of Science and Technology of China, Hefei, Anhui 230026, China
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Ishimoto Y, Ide S, Watanabe K, Oyu K, Kasai S, Umemura Y, Sasaki M, Nagaya H, Tatsuo S, Nozaki A, Ikushima Y, Wakayama T, Asano K, Saito A, Tomiyama M, Kakeda S. Usefulness of pituitary high-resolution 3D MRI with deep-learning-based reconstruction for perioperative evaluation of pituitary adenomas. Neuroradiology 2024; 66:937-945. [PMID: 38374411 DOI: 10.1007/s00234-024-03315-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 02/12/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence (CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma and parasellar regions on contrast-enhanced MRI. METHODS We evaluated 24 patients with pituitary adenoma or residual tumor using CUBE with and without DLR, 1-mm slice thickness 2D T1WI (1-mm 2D T1WI) with DLR, and 3D spoiled gradient echo sequence (SPGR) as contrast-enhanced MRI. Depiction scores of pituitary adenoma and parasellar regions were assigned by two neuroradiologists, and contrast-to-noise ratio (CNR) was calculated. RESULTS CUBE with DLR showed significantly higher scores for depicting pituitary adenoma or residual tumor compared to CUBE without DLR, 1-mm 2D T1WI with DLR, and SPGR (p < 0.01). The depiction score for delineation of the boundary between adenoma and the cavernous sinus was higher for CUBE with DLR than for 1-mm 2D T1WI with DLR (p = 0.01), but the difference was not significant when compared to SPGR (p = 0.20). CUBE with DLR had better interobserver agreement for evaluating adenomas than 1-mm 2D T1WI with DLR (Kappa values, 0.75 vs. 0.41). The CNR of the adenoma to the brain parenchyma increased to a ratio of 3.6 (obtained by dividing 13.7, CNR of CUBE with DLR, by 3.8, that without DLR, p < 0.01). CUBE with DLR had a significantly higher CNR than SPGR, but not 1-mm 2D T1WI with DLR. CONCLUSION On the contrast-enhanced MRI, compared to CUBE without DLR, 1-mm 2D T1WI with DLR and SPGR, CUBE with DLR improves the depiction of pituitary adenoma and parasellar regions.
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Affiliation(s)
- Yuka Ishimoto
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Satoru Ide
- Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Kazuhiko Oyu
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Sera Kasai
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Yoshihito Umemura
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Miho Sasaki
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Haruka Nagaya
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | - Soichiro Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
| | | | | | | | - Kenichiro Asano
- Department of Neurosurgery, Hirosaki University School of Medicine, Hirosaki, Aomori, Japan
| | - Atsushi Saito
- Department of Neurosurgery, Hirosaki University School of Medicine, Hirosaki, Aomori, Japan
| | - Masahiko Tomiyama
- Department of Neurology, Hirosaki University School of Medicine, Hirosaki, Aomori, Japan
| | - Shingo Kakeda
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori, Japan
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Kim J, Lee W, Kang B, Seo H, Park H. A noise robust image reconstruction using slice aware cycle interpolator network for parallel imaging in MRI. Med Phys 2024; 51:4143-4157. [PMID: 38598259 DOI: 10.1002/mp.17066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/01/2024] [Accepted: 03/23/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Reducing Magnetic resonance imaging (MRI) scan time has been an important issue for clinical applications. In order to reduce MRI scan time, imaging acceleration was made possible by undersampling k-space data. This is achieved by leveraging additional spatial information from multiple, independent receiver coils, thereby reducing the number of sampled k-space lines. PURPOSE The aim of this study is to develop a deep-learning method for parallel imaging with a reduced number of auto-calibration signals (ACS) lines in noisy environments. METHODS A cycle interpolator network is developed for robust reconstruction of parallel MRI with a small number of ACS lines in noisy environments. The network estimates missing (unsampled) lines of each coil data, and these estimated missing lines are then utilized to re-estimate the sampled k-space lines. In addition, a slice aware reconstruction technique is developed for noise-robust reconstruction while reducing the number of ACS lines. We conducted an evaluation study using retrospectively subsampled data obtained from three healthy volunteers at 3T MRI, involving three different slice thicknesses (1.5, 3.0, and 4.5 mm) and three different image contrasts (T1w, T2w, and FLAIR). RESULTS Despite the challenges posed by substantial noise in cases with a limited number of ACS lines and thinner slices, the slice aware cycle interpolator network reconstructs the enhanced parallel images. It outperforms RAKI, effectively eliminating aliasing artifacts. Moreover, the proposed network outperforms GRAPPA and demonstrates the ability to successfully reconstruct brain images even under severe noisy conditions. CONCLUSIONS The slice aware cycle interpolator network has the potential to improve reconstruction accuracy for a reduced number of ACS lines in noisy environments.
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Affiliation(s)
- Jeewon Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Bionics Research Center, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Wonil Lee
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Beomgu Kang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyunseok Seo
- Bionics Research Center, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - HyunWook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
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Lee Y, Yoon S, Paek M, Han D, Choi MH, Park SH. Advanced MRI techniques in abdominal imaging. Abdom Radiol (NY) 2024:10.1007/s00261-024-04369-7. [PMID: 38802629 DOI: 10.1007/s00261-024-04369-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/30/2024] [Accepted: 05/03/2024] [Indexed: 05/29/2024]
Abstract
Magnetic resonance imaging (MRI) is a crucial modality for abdominal imaging evaluation of focal lesions and tissue properties. However, several obstacles, such as prolonged scan times, limitations in patients' breath-hold capacity, and contrast agent-associated artifacts, remain in abdominal MR images. Recent techniques, including parallel imaging, three-dimensional acquisition, compressed sensing, and deep learning, have been developed to reduce the scan time while ensuring acceptable image quality or to achieve higher resolution without extending the scan duration. Quantitative measurements using MRI techniques enable the noninvasive evaluation of specific materials. A comprehensive understanding of these advanced techniques is essential for accurate interpretation of MRI sequences. Herein, we therefore review advanced abdominal MRI techniques.
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Affiliation(s)
- Yoonhee Lee
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - Sungjin Yoon
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | | | - Dongyeob Han
- Siemens Healthineers Ltd, Seoul, Republic of Korea
| | - Moon Hyung Choi
- Department of Radiology, Catholic University of Korea Eunpyeong St Mary's Hospital, Seoul, Republic of Korea
| | - So Hyun Park
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea.
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Yao H, Jia B, Pan X, Sun J. Validation and Feasibility of Ultrafast Cervical Spine MRI Using a Deep Learning-Assisted 3D Iterative Image Enhancement System. J Multidiscip Healthc 2024; 17:2499-2509. [PMID: 38799011 PMCID: PMC11128255 DOI: 10.2147/jmdh.s465002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/13/2024] [Indexed: 05/29/2024] Open
Abstract
Purpose This study aimed to evaluate the feasibility of ultrafast (2 min) cervical spine MRI protocol using a deep learning-assisted 3D iterative image enhancement (DL-3DIIE) system, compared to a conventional MRI protocol (6 min 14s). Patients and Methods Fifty-one patients were recruited and underwent cervical spine MRI using conventional and ultrafast protocols. A DL-3DIIE system was applied to the ultrafast protocol to compensate for the spatial resolution and signal-to-noise ratio (SNR) of images. Two radiologists independently assessed and graded the quality of images from the dimensions of artifacts, boundary sharpness, visibility of lesions and overall image quality. We recorded the presence or absence of different pathologies. Moreover, we examined the interchangeability of the two protocols by computing the 95% confidence interval of the individual equivalence index, and also evaluated the inter-protocol intra-observer agreement using Cohen's weighted kappa. Results Ultrafast-DL-3DIIE images were significantly better than conventional ones for artifacts and equivalent for other qualitative features. The number of cases with different kinds of pathologies was indistinguishable based on the MR images from ultrafast-DL-3DIIE and conventional protocols. With the exception of disc degeneration, the 95% confidence interval for the individual equivalence index across all variables did not surpass 5%, suggesting that the two protocols are interchangeable. The kappa values of these evaluations by the two radiologists ranged from 0.65 to 0.88, indicating good-to-excellent agreement. Conclusion The DL-3DIIE system enables 67% spine MRI scan time reduction while obtaining at least equivalent image quality and diagnostic results compared to the conventional protocol, suggesting its potential for clinical utility.
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Affiliation(s)
- Hui Yao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Bangsheng Jia
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Xuelin Pan
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Jiayu Sun
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, People’s Republic of China
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Yoon S, Shim YS, Park SH, Sung J, Nickel MD, Kim YJ, Lee HY, Kim HJ. Hepatobiliary phase imaging in cirrhotic patients using compressed sensing and controlled aliasing in parallel imaging results in higher acceleration. Eur Radiol 2024; 34:2233-2243. [PMID: 37731096 DOI: 10.1007/s00330-023-10226-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 07/19/2023] [Accepted: 07/27/2023] [Indexed: 09/22/2023]
Abstract
OBJECTIVE We aimed to compare the image quality and focal lesion detection ability of hepatobiliary phase (HBP) images obtained using compressed sensing (CS) and controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) in patients with liver cirrhosis. MATERIALS AND METHODS We retrospectively included 244 gadoxetic acid-enhanced liver MRI from 244 patients with cirrhosis obtained by two HBP images using CS and CAIPIRINHA from July 2020 to December 2020. The optimized resolution and scan time for CS-HBP and CAIPIRINHA-HBP were 0.9 × 0.9 × 1.5 mm3 and 15 s and 1.3 × 1.3 × 3 mm3 and 16 s, respectively. We compared the image quality between the two sets of images in 244 patients and focal lesion (n = 294) analyses for 112 patients. RESULTS CS-HBP showed comparable overall image quality (3.7 ± 0.9 vs. 3.6 ± 0.8, p = 0.680), superior liver edge sharpness (3.9 ± 0.6 vs. 3.6 ± 0.5, p < 0.001), and fewer respiratory motion artifacts (4.0 ± 0.7 vs. 3.8 ± 0.5, p < 0.001), but higher non-respiratory artifacts (3.4 ± 0.7 vs. 3.6 ± 0.6, p < 0.001) and subjective image noise (3.5 ± 0.8 vs. 3.6 ± 0.7, p = 0.014) than CAIPIRINHA-HBP. CS-HBP showed a higher signal-to-noise ratio in the liver than CAIPIRINHA-HBP (20.9 ± 9.0 vs. 18.9 ± 7.1, p = 0.008). The pooled sensitivity, specificity, and AUC were 90.0%, 77.5%, and 0.84 for CS-HBP and 73.5%, 82.4%, and 0.78 for CAIPIRINHA-HBP, respectively. CONCLUSIONS CS-HBP showed better focal lesion detection ability, comparable overall image quality, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and noise compared to CAIPIRINHA-HBP. Thus, CS-HBP could be recommended for liver MRI in patients with cirrhosis to improve diagnostic performance. CLINICAL RELEVANCE STATEMENT Thin-slice CS-HBP may be useful for detecting sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A while maintaining comparable subjective image quality. KEY POINTS • Compared with controlled aliasing in parallel imaging results in higher acceleration, compressed sensing hepatobiliary phase yielded thinner slices and shorter scan time at a higher accelerating factor. • Compressed sensing hepatobiliary phase showed comparable overall image quality, superior liver edge sharpness, and fewer respiratory motion artifacts, but higher non-respiratory artifacts and subjective image noise than controlled aliasing in parallel imaging results in higher acceleration-hepatobiliary phase. • Compressed sensing hepatobiliary phase can detect sub-centimeter hepatocellular carcinoma in cirrhotic patients with Child-Pugh classification A.
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Affiliation(s)
- Sungjin Yoon
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - Young Sup Shim
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - So Hyun Park
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea.
| | - Jaekon Sung
- Siemens Healthineers Ltd., Seoul, Republic of Korea
| | | | - Ye Jin Kim
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - Hee Young Lee
- Department of Radiology, Gil Medical Center, Gachon University College of Medicine, 21, Namdong-daero 774 Beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - Hwa Jung Kim
- Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea
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Ganesh VKSV, Kamepalli HK, Sharma DP, Thomas B, Kesavadas C. Multi-contrast echo-planar imaging sequence (Echo-planar imaging mix) in clinical situations demanding faster MRI-brain scans. J Neurosci Rural Pract 2024; 15:341-348. [PMID: 38746507 PMCID: PMC11090545 DOI: 10.25259/jnrp_508_2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 03/10/2024] [Indexed: 05/16/2024] Open
Abstract
Objectives The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41-1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (>90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient.
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Affiliation(s)
- Viswanadh Kalaparti Sri Venkata Ganesh
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Hari Kishore Kamepalli
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | | | - Bejoy Thomas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
| | - Chandrasekharan Kesavadas
- Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
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Wang Q, Zhao W, Xing X, Wang Y, Xin P, Chen Y, Zhu Y, Xu J, Zhao Q, Yuan H, Lang N. Feasibility of AI-assisted compressed sensing protocols in knee MR imaging: a prospective multi-reader study. Eur Radiol 2023; 33:8585-8596. [PMID: 37382615 PMCID: PMC10667384 DOI: 10.1007/s00330-023-09823-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/02/2023] [Accepted: 03/22/2023] [Indexed: 06/30/2023]
Abstract
OBJECTIVES To evaluate the image quality and diagnostic performance of AI-assisted compressed sensing (ACS) accelerated two-dimensional fast spin-echo MRI compared with standard parallel imaging (PI) in clinical 3.0T rapid knee scans. METHODS This prospective study enrolled 130 consecutive participants between March and September 2022. The MRI scan procedure included one 8.0-min PI protocol and two ACS protocols (3.5 min and 2.0 min). Quantitative image quality assessments were performed by evaluating edge rise distance (ERD) and signal-to-noise ratio (SNR). Shapiro-Wilk tests were performed and investigated by the Friedman test and post hoc analyses. Three radiologists independently evaluated structural disorders for each participant. Fleiss κ analysis was used to compare inter-reader and inter-protocol agreements. The diagnostic performance of each protocol was investigated and compared by DeLong's test. The threshold for statistical significance was set at p < 0.05. RESULTS A total of 150 knee MRI examinations constituted the study cohort. For the quantitative assessment of four conventional sequences with ACS protocols, SNR improved significantly (p < 0.001), and ERD was significantly reduced or equivalent to the PI protocol. For the abnormality evaluated, the intraclass correlation coefficient ranged from moderate to substantial between readers (κ = 0.75-0.98) and between protocols (κ = 0.73-0.98). For meniscal tears, cruciate ligament tears, and cartilage defects, the diagnostic performance of ACS protocols was considered equivalent to PI protocol (Delong test, p > 0.05). CONCLUSIONS Compared with the conventional PI acquisition, the novel ACS protocol demonstrated superior image quality and was feasible for achieving equivalent detection of structural abnormalities while reducing acquisition time by half. CLINICAL RELEVANCE STATEMENT Artificial intelligence-assisted compressed sensing (ACS) providing excellent quality and a 75% reduction in scanning time presents significant clinical advantages in improving the efficiency and accessibility of knee MRI for more patients. KEY POINTS • The prospective multi-reader study showed no difference in diagnostic performance between parallel imaging and AI-assisted compression sensing (ACS) was found. • Reduced scan time, sharper delineation, and less noise with ACS reconstruction. • Improved efficiency of the clinical knee MRI examination by the ACS acceleration.
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Affiliation(s)
- Qizheng Wang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Weili Zhao
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Xiaoying Xing
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Ying Wang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Peijin Xin
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Yongye Chen
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Yupeng Zhu
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Jiajia Xu
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Qiang Zhao
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China
| | - Ning Lang
- Department of Radiology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Beijing, 100191, People's Republic of China.
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Debs P, Fayad LM. The promise and limitations of artificial intelligence in musculoskeletal imaging. FRONTIERS IN RADIOLOGY 2023; 3:1242902. [PMID: 37609456 PMCID: PMC10440743 DOI: 10.3389/fradi.2023.1242902] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 07/26/2023] [Indexed: 08/24/2023]
Abstract
With the recent developments in deep learning and the rapid growth of convolutional neural networks, artificial intelligence has shown promise as a tool that can transform several aspects of the musculoskeletal imaging cycle. Its applications can involve both interpretive and non-interpretive tasks such as the ordering of imaging, scheduling, protocoling, image acquisition, report generation and communication of findings. However, artificial intelligence tools still face a number of challenges that can hinder effective implementation into clinical practice. The purpose of this review is to explore both the successes and limitations of artificial intelligence applications throughout the muscuskeletal imaging cycle and to highlight how these applications can help enhance the service radiologists deliver to their patients, resulting in increased efficiency as well as improved patient and provider satisfaction.
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Affiliation(s)
- Patrick Debs
- The Russell H. Morgan Department of Radiology & Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, MD, United States
| | - Laura M. Fayad
- The Russell H. Morgan Department of Radiology & Radiological Science, The Johns Hopkins Medical Institutions, Baltimore, MD, United States
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Ehmig J, Engel G, Lotz J, Lehmann W, Taheri S, Schilling AF, Seif Amir Hosseini A, Panahi B. MR-Imaging in Osteoarthritis: Current Standard of Practice and Future Outlook. Diagnostics (Basel) 2023; 13:2586. [PMID: 37568949 PMCID: PMC10417111 DOI: 10.3390/diagnostics13152586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/30/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023] Open
Abstract
Osteoarthritis (OA) is a common degenerative joint disease that affects millions of people worldwide. Magnetic resonance imaging (MRI) has emerged as a powerful tool for the evaluation and monitoring of OA due to its ability to visualize soft tissues and bone with high resolution. This review aims to provide an overview of the current state of MRI in OA, with a special focus on the knee, including protocol recommendations for clinical and research settings. Furthermore, new developments in the field of musculoskeletal MRI are highlighted in this review. These include compositional MRI techniques, such as T2 mapping and T1rho imaging, which can provide additional important information about the biochemical composition of cartilage and other joint tissues. In addition, this review discusses semiquantitative joint assessment based on MRI findings, which is a widely used method for evaluating OA severity and progression in the knee. We analyze the most common scoring methods and discuss potential benefits. Techniques to reduce acquisition times and the potential impact of deep learning in MR imaging for OA are also discussed, as these technological advances may impact clinical routine in the future.
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Affiliation(s)
- Jonathan Ehmig
- Institute of Diagnostic and Interventional Radiology, University Medical Center Göttingen, 37075 Göttingen, Germany; (J.E.); (G.E.)
| | - Günther Engel
- Institute of Diagnostic and Interventional Radiology, University Medical Center Göttingen, 37075 Göttingen, Germany; (J.E.); (G.E.)
| | - Joachim Lotz
- Institute of Diagnostic and Interventional Radiology, University Medical Center Göttingen, 37075 Göttingen, Germany; (J.E.); (G.E.)
| | - Wolfgang Lehmann
- Clinic of Trauma, Orthopedics and Reconstructive Surgery, Georg-August-University of Göttingen, 37075 Göttingen, Germany
| | - Shahed Taheri
- Clinic of Trauma, Orthopedics and Reconstructive Surgery, Georg-August-University of Göttingen, 37075 Göttingen, Germany
| | - Arndt F. Schilling
- Clinic of Trauma, Orthopedics and Reconstructive Surgery, Georg-August-University of Göttingen, 37075 Göttingen, Germany
| | - Ali Seif Amir Hosseini
- Institute of Diagnostic and Interventional Radiology, University Medical Center Göttingen, 37075 Göttingen, Germany; (J.E.); (G.E.)
| | - Babak Panahi
- Institute of Diagnostic and Interventional Radiology, University Medical Center Göttingen, 37075 Göttingen, Germany; (J.E.); (G.E.)
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11
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Xu Y, Farris CW, Anderson SW, Zhang X, Brown KA. Bayesian reconstruction of magnetic resonance images using Gaussian processes. Sci Rep 2023; 13:12527. [PMID: 37532743 PMCID: PMC10397278 DOI: 10.1038/s41598-023-39533-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/26/2023] [Indexed: 08/04/2023] Open
Abstract
A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations such as parallel imaging, compressed sensing, and deep learning-based reconstruction. Here, we propose and demonstrate a Bayesian method to build statistical libraries of magnetic resonance (MR) images in k-space and use these libraries to identify optimal subsampling paths and reconstruction processes. Specifically, we compute a multivariate normal distribution based upon Gaussian processes using a publicly available library of T1-weighted images of healthy brains. We combine this library with physics-informed envelope functions to only retain meaningful correlations in k-space. This covariance function is then used to select a series of ring-shaped subsampling paths using Bayesian optimization such that they optimally explore space while remaining practically realizable in commercial MRI systems. Combining optimized subsampling paths found for a range of images, we compute a generalized sampling path that, when used for novel images, produces superlative structural similarity and error in comparison to previously reported reconstruction processes (i.e. 96.3% structural similarity and < 0.003 normalized mean squared error from sampling only 12.5% of the k-space data). Finally, we use this reconstruction process on pathological data without retraining to show that reconstructed images are clinically useful for stroke identification. Since the model trained on images of healthy brains could be directly used for predictions in pathological brains without retraining, it shows the inherent transferability of this approach and opens doors to its widespread use.
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Affiliation(s)
- Yihong Xu
- Department of Physics, Boston University, Boston, MA, 02215, USA
| | - Chad W Farris
- Department of Radiology, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Stephan W Anderson
- Department of Radiology, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Xin Zhang
- Department of Mechanical Engineering, Boston University, Boston, MA, 02215, USA
- Department of Electrical & Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Division of Materials Science & Engineering, Boston University, Boston, MA, 02215, USA
| | - Keith A Brown
- Department of Physics, Boston University, Boston, MA, 02215, USA.
- Department of Mechanical Engineering, Boston University, Boston, MA, 02215, USA.
- Division of Materials Science & Engineering, Boston University, Boston, MA, 02215, USA.
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12
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Li T, Wang J, Yang Y, Glide-Hurst CK, Wen N, Cai J. Multi-parametric MRI for radiotherapy simulation. Med Phys 2023; 50:5273-5293. [PMID: 36710376 PMCID: PMC10382603 DOI: 10.1002/mp.16256] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 09/10/2022] [Accepted: 12/06/2022] [Indexed: 01/31/2023] Open
Abstract
Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.
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Affiliation(s)
- Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Jihong Wang
- Department of Radiation Physics, Division of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Yingli Yang
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong Univeristy School of Medicine, Shanghai, China
- SJTU-Ruijing-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Carri K Glide-Hurst
- Department of Radiation Oncology, University of Wisconsin, Madison, Wisconsin, USA
| | - Ning Wen
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong Univeristy School of Medicine, Shanghai, China
- SJTU-Ruijing-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- The Global Institute of Future Technology, Shanghai Jiaotong University, Shanghai, China
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
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13
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Nagpal P, Grist TM. MR Angiography: Contrast-Enhanced Acquisition Techniques. Magn Reson Imaging Clin N Am 2023; 31:493-501. [PMID: 37414474 DOI: 10.1016/j.mric.2023.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
Contrast-enhanced MR angiography (CE-MRA) is a frequently used MR imaging technique for evaluating cardiovascular structures. In many ways, it is similar to contrast-enhanced computed tomography (CT) angiography, except a gadolinium-based contrast agent (instead of iodinated contrast) is injected. Although the physiological principles of contrast injection overlap, the technical factors behind enhancement and image acquisition are different. CE-MRA provides an excellent alternative to CT for vascular evaluation and follow-up without requiring nephrotoxic contrast and ionizing radiation. This review describes the physical principles, limitations, and technical applications of CE-MRA techniques.
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Affiliation(s)
- Prashant Nagpal
- Cardiovascular Imaging, Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53705, USA.
| | - Thomas M Grist
- Radiology, University of Wisconsin Madison, E3/366 600 Highland Avenue, Madison, WI 53792, USA
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14
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Hahn S, Yi J, Lee HJ, Lee Y, Lee J, Wang X, Fung M. Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction. Skeletal Radiol 2023:10.1007/s00256-023-04321-8. [PMID: 36943429 DOI: 10.1007/s00256-023-04321-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/08/2023] [Accepted: 03/08/2023] [Indexed: 03/23/2023]
Abstract
OBJECTIVE To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based reconstruction (DLR) methods for evaluation of shoulder. MATERIALS AND METHODS We included patients who underwent conventional (acquisition time, 8 min) and accelerated (acquisition time, 4 min and 24 s; 45% reduction) PROPELLER shoulder MRI using both CR and DLR methods between February 2021 and February 2022 on a 3 T MRI system. Quantitative evaluation was performed by calculating the signal-to-noise ratio (SNR). Two musculoskeletal radiologists compared the image quality using conventional sequence with CR as the reference standard. Interobserver agreement between image sets for evaluating shoulder was analyzed using weighted/unweighted kappa statistics. RESULTS Ninety-two patients with 100 shoulder MRI scans were included. Conventional sequence with DLR had the highest SNR (P < .001), followed by accelerated sequence with DLR, conventional sequence with CR, and accelerated sequence with CR. Comparison of image quality by both readers revealed that conventional sequence with DLR (P = .003 and P < .001) and accelerated sequence with DLR (P = .016 and P < .001) had better image quality than the conventional sequence with CR. Interobserver agreement was substantial to almost perfect for detecting shoulder abnormalities (κ = 0.600-0.884). Agreement between the image sets was substantial to almost perfect (κ = 0.691-1). CONCLUSION Accelerated PROPELLER with DLR showed even better image quality than conventional PROPELLER with CR and interobserver agreement for shoulder pathologies comparable to that of conventional PROPELLER with CR, despite the shorter scan time.
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Affiliation(s)
- Seok Hahn
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea, Republic of Korea
| | - Jisook Yi
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea, Republic of Korea.
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea, Republic of Korea
| | - Yedaun Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, South Korea, Republic of Korea
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15
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Ohashi A, Kataoka M, Iima M, Honda M, Ota R, Urushibata Y, Nickel MD, Toi M, Zackrisson S, Nakamoto Y. Comparison of Ultrafast Dynamic Contrast-Enhanced (DCE) MRI with Conventional DCE MRI in the Morphological Assessment of Malignant Breast Lesions. Diagnostics (Basel) 2023; 13:diagnostics13061105. [PMID: 36980417 PMCID: PMC10046990 DOI: 10.3390/diagnostics13061105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 03/01/2023] [Accepted: 03/07/2023] [Indexed: 03/17/2023] Open
Abstract
Ultrafast (UF) dynamic contrast-enhanced (DCE)-MRI offers the potential for a faster and, therefore, less expensive examination of breast lesions; however, there are no reports that have evaluated whether UF DCE-MRI can be used the same as conventional DCE-MRI in the reading of morphological information. This study evaluated the agreement in morphological information obtained from malignant breast mass lesions between UF DCE-MRI and conventional DCE-MRI. UF DCE-MRI data were obtained over the first 60 s post-contrast injection, followed by the conventional DCE images. Two readers evaluated the size and morphology of the lesions in the final phase of the UF DCE-MRI and the early phase of the conventional DCE-MRI. Inter-method agreement in morphological information was evaluated for the two readers using the intraclass correlation coefficient for size, and the kappa statistics for the morphological descriptors. Differences in the proportion of each descriptor were examined using Fisher’s test of independence. Most inter-method agreements were higher than substantial. UF DCE-MRI showed a circumscribed margin and homogeneous enhancement more often than conventional imaging. However, the percentages of readings showing the same morphology assessment between the UF DCE-MRI and conventional DCE-MRI were 71.2% (136/191) for Reader 1 and 69.1% (132/191) for Reader 2. We conclude that UF DCE-MRI may replace conventional DCE-MRI to evaluate the morphological information of malignant breast mass lesions.
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Affiliation(s)
- Akane Ohashi
- Department of Translational Medicine, Diagnostic Radiology, Lund University, 225 02 Malmö, Sweden
- Department of Imaging and Functional Medicine, Skåne University Hospital, 225 02 Malmö, Sweden
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
- Correspondence: ; Tel.: +81-75-751-3760
| | - Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
- Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital, Kyoto 606-8507, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
- Department of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka 553-0003, Japan
| | - Rie Ota
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
- Department of Radiology, Tenri Hospital, Nara 632-8552, Japan
| | | | | | - Masakazu Toi
- Department of Breast Surgery, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Sophia Zackrisson
- Department of Translational Medicine, Diagnostic Radiology, Lund University, 225 02 Malmö, Sweden
- Department of Imaging and Functional Medicine, Skåne University Hospital, 225 02 Malmö, Sweden
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
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16
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Puchnin V, Jandaliyeva A, Hurshkainen A, Solomakha G, Nikulin A, Petrova P, Lavrenteva A, Andreychenko A, Shchelokova A. Quadrature transceive wireless coil: Design concept and application for bilateral breast MRI at 1.5 T. Magn Reson Med 2023; 89:1251-1264. [PMID: 36336799 DOI: 10.1002/mrm.29507] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/20/2022] [Accepted: 10/09/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE Development of a novel quadrature inductively driven transceive wireless coil for breast MRI at 1.5 T. METHODS A quadrature wireless coil (HHMM-coil) design has been developed as a combination of two linearly polarized coils: a pair of 'metasolenoid' coils (MM-coil) and a pair of Helmholtz-type coils (HH-coil). The MM-coil consisted of an array of split-loop resonators. The HH-coil design included two electrically connected flat spirals. All the wireless coils were coupled to a whole-body birdcage coil. The HHMM-coil was studied and compared to the linear coils in terms of transmit and SAR efficiencies via numerical simulations. A prototype of HHMM-coil was built and tested on a 1.5 T scanner in a phantom and healthy volunteer. We also proposed an extended design of the HHMM-coil and compared its performance to a dedicated breast array. RESULTS Numerical simulations of the HHMM-coil with a female voxel model have shown more than a 2.5-fold increase in transmit efficiency and a 1.7-fold enhancement of SAR efficiency compared to the linearly polarized coils. Phantom and in vivo imaging showed good agreement with the numerical simulations. Moreover, the HHMM-coil provided good image quality, visualizing all areas of interest similar to a multichannel breast array with a 32% reduction in signal-to-noise ratio. CONCLUSION The proposed quadrature HHMM-coil allows the B 1 + $$ {\mathrm{B}}_1^{+} $$ -field to be significantly better focused in the region-of-interest compared to the linearly polarized coils. Thus, the HHMM-coil provides high-quality breast imaging on a 1.5 T scanner using a whole-body birdcage coil for transmit and receive.
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Affiliation(s)
- Viktor Puchnin
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
| | | | - Anna Hurshkainen
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
| | - Georgiy Solomakha
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
| | - Anton Nikulin
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
| | - Polina Petrova
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
| | - Anna Lavrenteva
- Medical Institute named after Berezin Sergey (MIBS), St. Petersburg, Russia
| | - Anna Andreychenko
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia.,Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow Health Care Department, Moscow, Russia
| | - Alena Shchelokova
- School of Physics and Engineering, ITMO University, St. Petersburg, Russia
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17
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Liu J, Li W, Li Z, Yang J, Wang K, Cao X, Qin N, Xue K, Dai Y, Wu P, Qiu J. Magnetic resonance shoulder imaging using deep learning-based algorithm. Eur Radiol 2023:10.1007/s00330-023-09470-x. [PMID: 36826500 DOI: 10.1007/s00330-023-09470-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/03/2023] [Accepted: 01/22/2023] [Indexed: 02/25/2023]
Abstract
OBJECTIVE To investigate the feasibility of deep learning-based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI). METHODS This retrospective study was approved by the local ethics committee. Seventy consecutive patients who had been examined with both DL-MRI and non-DL-MRI were enrolled for the image quality and lesion diagnosis comparison. Another 400 patients had been examined only with DL-MRI. Their images' quality was assessed by 20 radiologists using a satisfaction survey. The Kendall W test was performed to assess interobserver agreement. The Wilcoxon test was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreement were evaluated by kappa analysis. RESULTS The scan time of DL-MRI (6 min 1 s) was nearly 50% decreased compared with that of non-DL-MRI (11 min 25 s). The image quality was higher in both PDWI (4.85 ± 0.31 for DL, and 4.73 ± 0.29 for non-DL) and T2WI (4.95 ± 0.2 for DL, and 4.74 ± 0.41 for non-DL) of DL-MRI. Good interobserver agreement was found for the image quality of all the MR sequences on both DL-MRI (Kendall W: 0.588~0.902) and non-DL-MRI (Kendall W: 0751~0.865). Both the SNRs and |CNR| were significantly higher in PDWI and T2WI of DL-MRI. High interobserver and interstudy agreements for the lesions in non-DL-MRI and DL-MRI (kappa value = 0.913 to 1.000) were observed. The results of the image quality satisfaction survey in 400 patients receiving DL-MRI in the shoulder obtained 5 scores among all the radiologists. CONCLUSION Shoulder DL-MRI can greatly reduce the scan time, while improve imaging quality of PDWI and T2WI compared to non-DL-MRI. KEY POINTS • Shoulder 2D DL-MRI can greatly reduce the whole scan time and improve imaging quality of both PDWI and T2WI compared to conventional parallel MRI. • Shoulder 2D DL-MRI could be a clinical routine with greatly improved work efficiency in the future.
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Affiliation(s)
- Jing Liu
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Wei Li
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Ziyuan Li
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Junzhe Yang
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Ke Wang
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Xinming Cao
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Naishan Qin
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China
| | - Ke Xue
- Central Research Institute, United Imaging Healthcare, 2258 Chengbei Rd., Jiading District, Shanghai, 201807, China
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare, 2258 Chengbei Rd., Jiading District, Shanghai, 201807, China
| | - Peng Wu
- Central Research Institute, United Imaging Healthcare, 2258 Chengbei Rd., Jiading District, Shanghai, 201807, China
| | - Jianxing Qiu
- Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
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18
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Tolpadi AA, Bharadwaj U, Gao KT, Bhattacharjee R, Gassert FG, Luitjens J, Giesler P, Morshuis JN, Fischer P, Hein M, Baumgartner CF, Razumov A, Dylov D, van Lohuizen Q, Fransen SJ, Zhang X, Tibrewala R, de Moura HL, Liu K, Zibetti MVW, Regatte R, Majumdar S, Pedoia V. K2S Challenge: From Undersampled K-Space to Automatic Segmentation. Bioengineering (Basel) 2023; 10:bioengineering10020267. [PMID: 36829761 PMCID: PMC9952400 DOI: 10.3390/bioengineering10020267] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/01/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
Magnetic Resonance Imaging (MRI) offers strong soft tissue contrast but suffers from long acquisition times and requires tedious annotation from radiologists. Traditionally, these challenges have been addressed separately with reconstruction and image analysis algorithms. To see if performance could be improved by treating both as end-to-end, we hosted the K2S challenge, in which challenge participants segmented knee bones and cartilage from 8× undersampled k-space. We curated the 300-patient K2S dataset of multicoil raw k-space and radiologist quality-checked segmentations. 87 teams registered for the challenge and there were 12 submissions, varying in methodologies from serial reconstruction and segmentation to end-to-end networks to another that eschewed a reconstruction algorithm altogether. Four teams produced strong submissions, with the winner having a weighted Dice Similarity Coefficient of 0.910 ± 0.021 across knee bones and cartilage. Interestingly, there was no correlation between reconstruction and segmentation metrics. Further analysis showed the top four submissions were suitable for downstream biomarker analysis, largely preserving cartilage thicknesses and key bone shape features with respect to ground truth. K2S thus showed the value in considering reconstruction and image analysis as end-to-end tasks, as this leaves room for optimization while more realistically reflecting the long-term use case of tools being developed by the MR community.
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Affiliation(s)
- Aniket A. Tolpadi
- Department of Bioengineering, University of California, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Correspondence:
| | - Upasana Bharadwaj
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kenneth T. Gao
- Department of Bioengineering, University of California, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Rupsa Bhattacharjee
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Felix G. Gassert
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, 81675 Munich, Germany
| | - Johanna Luitjens
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology, Klinikum Großhadern, Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Paula Giesler
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jan Nikolas Morshuis
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | - Paul Fischer
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | - Matthias Hein
- Cluster of Excellence Machine Learning, University of Tübingen, 72076 Tübingen, Germany
| | | | - Artem Razumov
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Dmitry Dylov
- Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia
| | - Quintin van Lohuizen
- Department of Radiology, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | - Stefan J. Fransen
- Department of Radiology, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands
| | - Xiaoxia Zhang
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Radhika Tibrewala
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Hector Lise de Moura
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Kangning Liu
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Marcelo V. W. Zibetti
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ravinder Regatte
- Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
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19
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Tolpadi AA, Han M, Calivà F, Pedoia V, Majumdar S. Region of interest-specific loss functions improve T 2 quantification with ultrafast T 2 mapping MRI sequences in knee, hip and lumbar spine. Sci Rep 2022; 12:22208. [PMID: 36564430 PMCID: PMC9789075 DOI: 10.1038/s41598-022-26266-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
MRI T2 mapping sequences quantitatively assess tissue health and depict early degenerative changes in musculoskeletal (MSK) tissues like cartilage and intervertebral discs (IVDs) but require long acquisition times. In MSK imaging, small features in cartilage and IVDs are crucial for diagnoses and must be preserved when reconstructing accelerated data. To these ends, we propose region of interest-specific postprocessing of accelerated acquisitions: a recurrent UNet deep learning architecture that provides T2 maps in knee cartilage, hip cartilage, and lumbar spine IVDs from accelerated T2-prepared snapshot gradient-echo acquisitions, optimizing for cartilage and IVD performance with a multi-component loss function that most heavily penalizes errors in those regions. Quantification errors in knee and hip cartilage were under 10% and 9% from acceleration factors R = 2 through 10, respectively, with bias for both under 3 ms for most of R = 2 through 12. In IVDs, mean quantification errors were under 12% from R = 2 through 6. A Gray Level Co-Occurrence Matrix-based scheme showed knee and hip pipelines outperformed state-of-the-art models, retaining smooth textures for most R and sharper ones through moderate R. Our methodology yields robust T2 maps while offering new approaches for optimizing and evaluating reconstruction algorithms to facilitate better preservation of small, clinically relevant features.
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Affiliation(s)
- Aniket A Tolpadi
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA.
| | - Misung Han
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Francesco Calivà
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California, 1700, 4th Street, San Francisco, CA, 94158, USA
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Gallo-Bernal S, Bedoya MA, Gee MS, Jaimes C. Pediatric magnetic resonance imaging: faster is better. Pediatr Radiol 2022:10.1007/s00247-022-05529-x. [PMID: 36261512 DOI: 10.1007/s00247-022-05529-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/29/2022] [Accepted: 10/03/2022] [Indexed: 10/24/2022]
Abstract
Magnetic resonance imaging (MRI) has emerged as the preferred imaging modality for evaluating a wide range of pediatric medical conditions. Nevertheless, the long acquisition times associated with this technique can limit its widespread use in young children, resulting in motion-degraded or non-diagnostic studies. As a result, sedation or general anesthesia is often necessary to obtain diagnostic images, which has implications for the safety profile of MRI, the cost of the exam and the radiology department's clinical workflow. Over the last decade, several techniques have been developed to increase the speed of MRI, including parallel imaging, single-shot acquisition, controlled aliasing techniques, compressed sensing and artificial-intelligence-based reconstructions. These are advantageous because shorter examinations decrease the need for sedation and the severity of motion artifacts, increase scanner throughput, and improve system efficiency. In this review we discuss a framework for image acceleration in children that includes the synergistic use of state-of-the-art MRI hardware and optimized pulse sequences. The discussion is framed within the context of pediatric radiology and incorporates the authors' experience in deploying these techniques in routine clinical practice.
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Affiliation(s)
- Sebastian Gallo-Bernal
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - M Alejandra Bedoya
- Department of Radiology, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., 2nd floor, Main Building, Boston, MA, 02115, USA
| | - Michael S Gee
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Camilo Jaimes
- Department of Radiology, Harvard Medical School, Boston, MA, USA. .,Department of Radiology, Boston Children's Hospital, 300 Longwood Ave., 2nd floor, Main Building, Boston, MA, 02115, USA.
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21
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Kim HG, Oh SW, Han D, Kim JY, Lim GY. Accelerated 3D T2-weighted images using compressed sensing for pediatric brain imaging. Neuroradiology 2022; 64:2399-2407. [PMID: 35920890 DOI: 10.1007/s00234-022-03028-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 07/25/2022] [Indexed: 11/24/2022]
Abstract
PURPOSE The purpose of this study was to compare the image quality of the 3D T2-weighted images accelerated using conventional method (CAI-SPACE) with the images accelerated using compressed sensing (CS-SPACE) in pediatric brain imaging. METHODS A total of 116 brain MRI (53 with CAI-SPACE and 63 with CS-SPACE) were obtained from children 16 years old or younger. Quantitative image quality was evaluated using the apparent signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The sequences were qualitatively evaluated for overall image quality, general artifact, cerebrospinal fluid (CSF)-related artifact, and grey-white matter differentiation. The two sequences were compared for the total and two age groups (< 24 months vs. ≥ 24 months). RESULTS Compressed sensing application in 3D T2-weighted imaging resulted in 8.5% reduction in scanning time. Quantitative image quality analysis showed higher apparent SNR (median [Interquartile range]; 29 [25] vs. 23 [14], P = 0.005) and CNR (0.231 [0.121] vs. 0.165 [0.120], P = 0.027) with CS-SPACE compared to CAI-SPACE. Qualitative image quality analysis showed better image quality with CS-SPACE for general (P = 0.024) and CSF-related artifact (P < 0.001). CSF-related artifacts reduction was prominent in the older age group (≥ 24 months). Overall image quality (P = 0.162) and grey-white matter differentiation (P = 0.397) were comparable between CAI-SPACE and CS-SPACE. CONCLUSION Compressed sensing application in 3D T2-weighted images modestly reduced acquisition time and lowered CSF-related artifact compared to conventional images of the pediatric brain.
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Affiliation(s)
- Hyun Gi Kim
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Se Won Oh
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | - Jee Young Kim
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Gye Yeon Lim
- Department of Radiology, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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22
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Zhao Y, Peng C, Wang S, Liang X, Meng X. The feasibility investigation of AI -assisted compressed sensing in kidney MR imaging: an ultra-fast T2WI imaging technology. BMC Med Imaging 2022; 22:119. [PMID: 35787673 PMCID: PMC9254529 DOI: 10.1186/s12880-022-00842-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 05/31/2022] [Indexed: 11/27/2022] Open
Abstract
Object To explore the feasibility and clinical application of AI -assisted compressed sensing (ACS) technology in kidney MR imaging.
Methods 33 patients were enrolled in this study, affiliated to our hospital from September 2020 to April 2021. The patients underwent T2-weighed sequences of both the ACS scan and the conventional respiratory navigator (NAVI) scan. We evaluated the subjective image quality scores, including the sharpness of image edge, artifact and the overall image quality, and compared the objective image quality indicators such as scanning time, signal-to-noise ratio (SNR), and contrast signal-to-noise ratio (CNR). The Wilcoxon’s rank sum test and the paired t test were used to compare the image quality between ACS and NAVI groups. The p-value less than 0.05 indicated a statistically significant difference. Results The edge sharpness of the ACS group was significant lower than that of the NAVI group (p < 0.01), however, there were no significant differences in the artifact and the overall rating of image quality between the two groups (p > 0.05). In terms of the objective image quality scores, the scanning time of the ACS group is significantly lower than that of control group. The SNR and CNR of ACS group were significantly higher than those of NAVI group (SNR:3.63 ± 0.76 vs 3.04 ± 0.44, p < 0.001; CNR: 14.44 ± 4.53 vs 12.05 ± 3.32, p < 0.001). In addition, the subjective and objective measurement results of the two radiologists were in good agreement (ICC = 0.61–0.88). Conclusion ACS technology has obvious advantages when applied to kidney MR imaging, which can realize ultra-fast MR imaging. The images can be acquired with a single breath-hold (17 s), which greatly shortens the scanning time. Moreover, the image quality is equal to or better than the conventional technology, which can meet the diagnostic requirements. Thus, it has obvious advantages in diagnosis for kidney disease patients with different tolerance levels for the clinical promotion. Supplementary Information The online version contains supplementary material available at 10.1186/s12880-022-00842-1.
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Affiliation(s)
- Yanjie Zhao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chengdong Peng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Shaofang Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | | | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
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Kondo S, Nakamura Y, Higaki T, Nishihara T, Takizawa M, Shirai T, Fujimori M, Bito Y, Narita K, Sueoka T, Honda Y, Tani C, Awai K. Utility of Wavelet Denoising with Geometry Factor Weighting for Gadoxetic Acid-enhanced Hepatobiliary-phase MR Imaging. Magn Reson Med Sci 2022; 22:241-252. [PMID: 35650028 PMCID: PMC10086400 DOI: 10.2463/mrms.mp.2022-0041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
PURPOSE The wavelet denoising with geometry factor weighting (g-denoising) method can reduce the image noise by adapting to spatially varying noise levels induced by parallel imaging. The aim of this study was to investigate the clinical applicability of g-denoising on hepatobiliary-phase (HBP) images with gadoxetic acid. METHODS We subjected 53 patients suspected of harboring hepatic neoplastic lesions to gadoxetic acid-enhanced HBP imaging with and without g-denoising (g+HBP and g-HBP). The matrix size was reduced for g+HBP images to avoid prolonging the scanning time. Two radiologists calculated the SNR, the portal vein-, and paraspinal muscle contrast-to-noise ratio (CNR) relative to the hepatic parenchyma (liver-to-portal vein- and liver-to-muscle CNR). Two other radiologists independently graded the sharpness of the liver edge, the visibility of intrahepatic vessels, the image noise, the homogeneity of liver parenchyma, and the overall image quality using a 5-point scale. Differences between g-HBP and g+HBP images were determined with the two-sided Wilcoxon signed-rank test. RESULTS The liver-to-portal- and liver-to-muscle CNR and the SNR were significantly higher on g+HBP- than g-HBP images (P < 0.01), as was the qualitative score for the image noise, homogeneity of liver parenchyma, and overall image quality (P < 0.01). Although there were no significant differences in the scores for the sharpness of the liver edge or the score assigned for the visibility of intrahepatic vessels (P = 0.05, 0.43), with g+HBP the score was lower in three patients for the sharpness of the liver edge and in six patients for the visibility of intrahepatic vessels. CONCLUSION At gadoxetic acid-enhanced HBP imaging, g-denoising yielded a better image quality than conventional HBP imaging although the anatomic details may be degraded.
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Affiliation(s)
- Shota Kondo
- Department of Diagnostic Radiology, Hiroshima University
| | - Yuko Nakamura
- Department of Diagnostic Radiology, Hiroshima University
| | - Toru Higaki
- Department of Diagnostic Radiology, Hiroshima University
| | | | | | | | | | | | - Keigo Narita
- Department of Diagnostic Radiology, Hiroshima University
| | | | - Yukiko Honda
- Department of Diagnostic Radiology, Hiroshima University
| | - Chihiro Tani
- Department of Diagnostic Radiology, Hiroshima University
| | - Kazuo Awai
- Department of Diagnostic Radiology, Hiroshima University
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Kwok WE. Basic Principles of and Practical Guide to Clinical MRI Radiofrequency Coils. Radiographics 2022; 42:898-918. [PMID: 35394887 DOI: 10.1148/rg.210110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Radiofrequency (RF) coils are an essential MRI component used for transmission of the RF field to excite nuclear spins and for reception of the MRI signal. They play an important role in image quality in terms of signal-to-noise ratio, signal uniformity, and image resolution. However, they are also associated with potential image artifacts and RF heating that may lead to patient burns. Knowledge of the basic principles of RF coils-including coil designs commonly used in clinical MRI and the anatomy of RF receive coils-facilitates understanding of the use and safety issues of RF coils. Selection of suitable RF coils for individual applications and proper use of RF coils in particular MRI techniques such as parallel imaging are needed to achieve optimal image quality, prevent image artifacts, and reduce the risk of RF burns. The ability to correctly identify RF coil problems and distinguish them from other problems with image artifacts resembling those of RF coil problems allows effective handling of the problems and efficient clinical MRI operation. Quality control of RF coils is required to ensure consistent image quality for clinical MRI and avoid coil problems that may affect image diagnostic evaluation or interrupt patient imaging. There are different phantom test methods for RF coil quality control; the appropriate one to use depends on the coil design and MRI system. An invited commentary by Ohliger is available online. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Wingchi E Kwok
- From the Department of Imaging Sciences, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642; and University of Rochester Center for Advanced Brain Imaging and Neurophysiology, Rochester, NY
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25
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Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain. Neuroimage 2022; 255:119199. [PMID: 35417754 PMCID: PMC9195912 DOI: 10.1016/j.neuroimage.2022.119199] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 04/05/2022] [Accepted: 04/07/2022] [Indexed: 12/24/2022] Open
Abstract
Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 μm isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 μm isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 μm to 200 μm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.
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Vaish A, Rajwade A, Gupta A. TL-HARDI: Transform learning based accelerated reconstruction of HARDI data. Comput Biol Med 2022; 143:105212. [PMID: 35151154 DOI: 10.1016/j.compbiomed.2022.105212] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/17/2021] [Accepted: 01/02/2022] [Indexed: 11/03/2022]
Abstract
Diffusion magnetic resonance imaging (dMRI) is being extensively used to study the neural architecture of the brain. High angular resolution diffusion imaging (HARDI), a variant of diffusion MRI, measures the diffusion of water molecules along the angular gradient directions in the q-space. It provides better estimates of fiber orientations compared to the traditionally used diffusion tensor imaging (DTI). However, HARDI requires acquisition of relatively large number of samples leading to longer scanning times. Several approaches based on compressive sensing (CS) have been proposed to accelerate HARDI acquisition, leveraging on the sparse representation of the HARDI signal in a pre-specified sparsifying basis. In this paper, we propose to carry out reconstruction of compressively sensed HARDI data using an adaptively learned transform. The transform is learned (i) from the compressive measurements on-the-fly, thereby, eliminating the overhead of choosing fixed sparsifying transforms, and (ii) on overlapping patches of the data, thereby, capturing local image structure effectively. Experiments are conducted on multiple real HARDI data for varying sampling ratios and sampling schemes. The performance of the proposed "TL-HARDI" method is compared with the state-of-the-art methods on various known image quality metrics as well as on dMRI feature maps derived from the reconstructed images. The proposed method is observed to yield better reconstruction than the existing state-of-the-art methods in both quantitative and qualitative comparisons.
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27
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Bardo DME, Rubert N. Radial sequences and compressed sensing in pediatric body magnetic resonance imaging. Pediatr Radiol 2022; 52:382-390. [PMID: 34009408 DOI: 10.1007/s00247-021-05097-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 03/11/2021] [Accepted: 04/28/2021] [Indexed: 12/28/2022]
Abstract
Magnetic resonance imaging (MRI) is often an ideal imaging modality for children of any age for any anatomy and for many pathologies. MRI sequences can be prescribed to produce high-resolution images of anatomical structures, characterize tissue composition, and detect physiological states and organ function. Shortening imaging sequences in any manner possible has been a topic of research and development in MRI since its emergence. Selection of imaging sequence parameters influences more than just the appearance and signal qualities of the imaged tissues; these details along with spatial encoding and data readout steps determine the time it takes to acquire an image. As each piece of image data is acquired and encoded with spatial and temporal information it is stored in k-space. As k-space is filled, either completely or partially, a diagnostic image or physiological data can be reconstructed. Shortening the length of time required for the readout step by efficiently filling k-space using compressed sensing and radial techniques is the subject of this manuscript.
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Affiliation(s)
- Dianna M E Bardo
- Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA.
| | - Nicholas Rubert
- Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA
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28
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Jang JS, Lee HB, Suh CH, Lee MH. Image quality and acquisition time assessments for phase oversampling in compressed sensing sensitivity encoding: Comparison with conventional SENSE. J Appl Clin Med Phys 2021; 23:e13509. [PMID: 34953027 PMCID: PMC8833279 DOI: 10.1002/acm2.13509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 12/05/2021] [Accepted: 12/06/2021] [Indexed: 11/09/2022] Open
Abstract
This study compared sensitivity encoding (SENSE) and compressed sensing sensitivity encoding (CS-SENSE) for phase oversampling distance and assessed its impact on image quality and image acquisition time. The experiment was performed with a large diameter phantom using 16-channel anterior body coils. All imaging data were divided into three groups according to the parallel imaging technique and oversampling distances: groups A (SENSE with phase oversampling distance of 150 mm), B (CS-SENSE with phase oversampling distance of 100 mm), and C (CS-SENSE with phase oversampling distance of 75 mm). No statistically significant differences were observed among groups A, B, and C regarding both T2 and T1 turbo spin-echo (TSE) sequences using an acceleration factor (AF) of 2 (p = 0.301 and 0.289, respectively). In comparison with AF 2 of group A, the scan time of AF 2 of groups B and C was reduced by 11.2% and 23.5% (T2 TSE) and 15.8% and 22.7% (T1 TSE), respectively, while providing comparable image quality. Significant image noise and aliasing artifact were more evident at AF ≥ 2 in group A compared with groups B and C. CS-SENSE with a less phase oversampling distance can reduce image acquisition time without image quality degradation compared with that of SENSE, despite the increase in aliasing artifact as the AF increased in both CS-SENSE and SENSE.
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Affiliation(s)
- Ji Sung Jang
- Departments of Radiology and Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, South Korea
| | - Ho Beom Lee
- Departments of Radiology and Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, South Korea
| | - Chong Hyun Suh
- Departments of Radiology and Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, South Korea
| | - Min Hee Lee
- Departments of Radiology and Research Institute of Radiology, Asan Medical Center, College of Medicine, University of Ulsan, South Korea
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Kim S, Park C, Kim KS, Jeong HS, Lee SM. Clinical feasibility of simultaneous multislice acceleration in knee MRI. Clin Imaging 2021; 82:216-223. [PMID: 34896934 DOI: 10.1016/j.clinimag.2021.11.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 11/13/2021] [Accepted: 11/27/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To find the best simultaneous multislice (SMS) accelerated setting for clinical application in knee MRI. MATERIAL AND METHODS Thirty-three patients (mean age, 54 years; 21 women) who underwent knee MRI (conventional/SMS sequences) between June and October 2020 were enrolled. Two radiologists retrospectively evaluated sagittal T1- and T2-weighted conventional (2-fold parallel acquisition technique [PAT-2]) and SMS (SMS-2 [PAT-2 with 2-fold SMS], SMS-3, and SMS-4) images. For qualitative analysis, artifacts (zebra/residual aliasing) and diagnostic confidence for internal derangement of knee (bone marrow, cartilage, meniscus, anterior cruciate ligament, and synovium abnormalities) were evaluated. For quantitative analysis, contrast-to-noise ratios of bone marrow, meniscus, joint effusion, and ligament were evaluated. RESULTS Compared to PAT-2 (2 min 32 s), mean acquisition time was reduced by 47% in SMS-2; 64%, SMS-3; and 70%, SMS-4. In qualitative analysis, zebra artifacts were only seen on T2-weighted SMS images. The more SMS was applied, the more zebra and residual aliasing artifacts were seen and the lower diagnostic confidence was for internal derangement. However, qualitative analysis showed acceptable image quality in SMS-2 and SMS-3 images, but not in SMS-4 images. In quantitative analysis, SMS-4 images showed the lowest contrast-to-noise ratios and there were no significant differences among PAT-2, SMS-2, and SMS-3 images. CONCLUSION Applying SMS-3 to knee MRI reduced scan time and showed acceptable image quality compared to conventional (PAT-2). However, when evaluating SMS images, radiologists should know that when more SMS is applied, more zebra and residual aliasing artifacts appear.
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Affiliation(s)
- Shinyoung Kim
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Chankue Park
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea.
| | | | - Hee Seok Jeong
- Department of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Sang-Min Lee
- Department Orthopedic Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
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Samreen N, Mercado C, Heacock L, Chacko C, Partridge SC, Chhor C. Screening Breast MRI Primer: Indications, Current Protocols, and Emerging Techniques. JOURNAL OF BREAST IMAGING 2021; 3:387-398. [PMID: 38424773 DOI: 10.1093/jbi/wbaa116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Indexed: 03/02/2024]
Abstract
Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.
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Affiliation(s)
- Naziya Samreen
- New York University, Department of Radiology, Garden City, NY, USA
| | - Cecilia Mercado
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Laura Heacock
- NYU School of Medicine, Department of Radiology, New York, NY, USA
| | - Celin Chacko
- New York University, Department of Radiology, Garden City, NY, USA
| | | | - Chloe Chhor
- NYU School of Medicine, Department of Radiology, New York, NY, USA
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Koktzoglou I, Huang R, Ankenbrandt WJ, Walker MT, Edelman RR. Super-resolution head and neck MRA using deep machine learning. Magn Reson Med 2021; 86:335-345. [PMID: 33619802 DOI: 10.1002/mrm.28738] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/25/2021] [Accepted: 01/26/2021] [Indexed: 12/29/2022]
Abstract
PURPOSE To probe the feasibility of deep learning-based super-resolution (SR) reconstruction applied to nonenhanced MR angiography (MRA) of the head and neck. METHODS High-resolution 3D thin-slab stack-of-stars quiescent interval slice-selective (QISS) MRA of the head and neck was obtained in eight subjects (seven healthy volunteers, one patient) at 3T. The spatial resolution of high-resolution ground-truth MRA data in the slice-encoding direction was reduced by factors of 2 to 6. Four deep neural network (DNN) SR reconstructions were applied, with two based on U-Net architectures (2D and 3D) and two (2D and 3D) consisting of serial convolutions with a residual connection. SR images were compared to ground-truth high-resolution data using Dice similarity coefficient (DSC), structural similarity index measure (SSIM), arterial diameter, and arterial sharpness measurements. Image review of the optimal DNN SR reconstruction was done by two experienced neuroradiologists. RESULTS DNN SR of up to twofold and fourfold lower-resolution (LR) input volumes provided images that resembled those of the original high-resolution ground-truth volumes for intracranial and extracranial arterial segments, and improved DSC, SSIM, arterial diameters, and arterial sharpness relative to LR volumes (P < .001). The 3D DNN SR outperformed 2D DNN SR reconstruction. According to two neuroradiologists, 3D DNN SR reconstruction consistently improved image quality with respect to LR input volumes (P < .001). CONCLUSION DNN-based SR reconstruction of 3D head and neck QISS MRA offers the potential for up to fourfold reduction in acquisition time for neck vessels without the need to commensurately sacrifice spatial resolution.
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Affiliation(s)
- Ioannis Koktzoglou
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, USA.,Pritzker School of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Rong Huang
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - William J Ankenbrandt
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, USA.,Pritzker School of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Matthew T Walker
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, USA.,Pritzker School of Medicine, University of Chicago, Chicago, Illinois, USA
| | - Robert R Edelman
- Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, USA.,Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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Safety challenges related to the use of sedation and general anesthesia in pediatric patients undergoing magnetic resonance imaging examinations. Pediatr Radiol 2021; 51:724-735. [PMID: 33860861 PMCID: PMC8049862 DOI: 10.1007/s00247-021-05044-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 01/17/2021] [Accepted: 03/01/2021] [Indexed: 12/17/2022]
Abstract
The use of sedation and general anesthesia has facilitated the significant growth of MRI use among children over the last years. While sedation and general anesthesia are considered to be relatively safe, their use poses potential risks in the short term and in the long term. This manuscript reviews the reasons why MRI examinations require sedation and general anesthesia more commonly in the pediatric population, summarizes the safety profile of sedation and general anesthesia, and discusses an amalgam of strategies that can be implemented and can ultimately lead to the optimization of sedation and general anesthesia care within pediatric radiology departments.
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Hajhosseiny R, Bustin A, Munoz C, Rashid I, Cruz G, Manning WJ, Prieto C, Botnar RM. Coronary Magnetic Resonance Angiography: Technical Innovations Leading Us to the Promised Land? JACC Cardiovasc Imaging 2020; 13:2653-2672. [PMID: 32199836 DOI: 10.1016/j.jcmg.2020.01.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 01/03/2020] [Accepted: 01/08/2020] [Indexed: 02/07/2023]
Abstract
Coronary artery disease remains the leading cause of cardiovascular morbidity and mortality. Invasive X-ray angiography and coronary computed tomography angiography are established gold standards for coronary luminography. However, they expose patients to invasive complications, ionizing radiation, and iodinated contrast agents. Among a number of imaging modalities, coronary cardiovascular magnetic resonance (CMR) angiography may be used in some cases as an alternative for the detection and monitoring of coronary arterial stenosis, with advantages including its versatility, excellent soft tissue characterization, and avoidance of ionizing radiation and iodinated contrast agents. In this review, we explore the recent advances in motion correction, image acceleration, and reconstruction technologies that are bringing coronary CMR angiography closer to widespread clinical implementation.
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Affiliation(s)
- Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Imran Rashid
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Warren J Manning
- Department of Medicine (Cardiovascular Division) and Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
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A multiparametric approach to diagnosing breast lesions using diffusion-weighted imaging and ultrafast dynamic contrast-enhanced MRI. Magn Reson Imaging 2020; 71:154-160. [DOI: 10.1016/j.mri.2020.04.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 02/06/2020] [Accepted: 04/12/2020] [Indexed: 12/30/2022]
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35
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Subhas N, Li H, Yang M, Winalski CS, Polster J, Obuchowski N, Mamoto K, Liu R, Zhang C, Huang P, Gaire SK, Liang D, Shen B, Li X, Ying L. Diagnostic interchangeability of deep convolutional neural networks reconstructed knee MR images: preliminary experience. Quant Imaging Med Surg 2020; 10:1748-1762. [PMID: 32879854 DOI: 10.21037/qims-20-664] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Background MRI acceleration using deep learning (DL) convolutional neural networks (CNNs) is a novel technique with great promise. Increasing the number of convolutional layers may allow for more accurate image reconstruction. Studies on evaluating the diagnostic interchangeability of DL reconstructed knee magnetic resonance (MR) images are scarce. The purpose of this study was to develop a deep CNN (DCNN) with an optimal number of layers for accelerating knee magnetic resonance imaging (MRI) acquisition by 6-fold and to test the diagnostic interchangeability and image quality of nonaccelerated images versus images reconstructed with a 15-layer DCNN or 3-layer CNN. Methods For the feasibility portion of this study, 10 patients were randomly selected from the Osteoarthritis Initiative (OAI) cohort. For the interchangeability portion of the study, 40 patients were randomly selected from the OAI cohort. Three readers assessed meniscal and anterior cruciate ligament (ACL) tears and cartilage defects using DCNN, CNN, and nonaccelerated images. Image quality was subjectively graded as nondiagnostic, poor, acceptable, or excellent. Interchangeability was tested by comparing the frequency of agreement when readers used both accelerated and nonaccelerated images to frequency of agreement when readers only used nonaccelerated images. A noninferiority margin of 0.10 was used to ensure type I error ≤5% and power ≥80%. A logistic regression model using generalized estimating equations was used to compare proportions; 95% confidence intervals (CIs) were constructed. Results DCNN and CNN images were interchangeable with nonaccelerated images for all structures, with excess disagreement values ranging from -2.5% [95% CI: (-6.1, 1.1)] to 3.0% [95% CI: (-0.1, 6.1)]. The quality of DCNN images was graded higher than that of CNN images but less than that of nonaccelerated images [excellent/acceptable quality: DCNN, 95% of cases (114/120); CNN, 60% (72/120); nonaccelerated, 97.5% (117/120)]. Conclusions Six-fold accelerated knee images reconstructed with a DL technique are diagnostically interchangeable with nonaccelerated images and have acceptable image quality when using a 15-layer CNN.
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Affiliation(s)
- Naveen Subhas
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Hongyu Li
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
| | - Mingrui Yang
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Carl S Winalski
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Joshua Polster
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Nancy Obuchowski
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Kenji Mamoto
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ruiying Liu
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
| | - Chaoyi Zhang
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
| | - Peizhou Huang
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
| | - Sunil Kumar Gaire
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Medical AI Research Center, SIAT, CAS, Shenzhen, China
| | - Bowen Shen
- Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
| | - Xiaojuan Li
- Program of Advanced Musculoskeletal Imaging (PAMI), Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA.,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Leslie Ying
- Department of Biomedical Engineering, Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, NY, USA
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Bedayat A, Hassani C, Prosper AE, Chalian H, Khoshpouri P, Ruehm SG. Recent Innovations in Renal Vascular Imaging. Radiol Clin North Am 2020; 58:781-796. [DOI: 10.1016/j.rcl.2020.02.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Abstract
Imaging of the biliary system has improved and has allowed MR to become a key noninvasive tool for evaluation of the biliary system. A variety of magnetic resonance cholangiopancreatography techniques have been developed, with improved visualization of the biliary system and biliary pathology. Key avenues of advancement include increasing the speed of acquisition, improving spatial resolution, and reducing artifacts. T1-weighted imaging using gadolinium-based hepatobiliary contrast agents allows for evaluation in additional indications, such as liver donor evaluation, biliary leak identification, and choledochal cyst confirmation. There is potential for further increased utility of MR in the evaluation of the biliary system.
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Affiliation(s)
| | - Frank H Miller
- Body Imaging Section and Fellowship, Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair, Suite 800, Chicago, IL 60611, USA
| | - Benjamin M Yeh
- University of California - San Francisco, 505 Parnassus Avenue, M391 Box 0628, San Francisco, CA 94143-0628, USA
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Dietz B, Yun J, Yip E, Gabos Z, Fallone BG, Wachowicz K. Single patient convolutional neural networks for real-time MR reconstruction: coherent low-resolution versus incoherent undersampling. ACTA ACUST UNITED AC 2020; 65:08NT03. [DOI: 10.1088/1361-6560/ab7d13] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Fast Phase-Contrast Cine MRI for Assessing Intracranial Hemodynamics and Cerebrospinal Fluid Dynamics. Diagnostics (Basel) 2020; 10:diagnostics10040241. [PMID: 32326291 PMCID: PMC7236008 DOI: 10.3390/diagnostics10040241] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/16/2020] [Accepted: 04/17/2020] [Indexed: 11/17/2022] Open
Abstract
We propose fast phase-contrast cine magnetic resonance imaging (PC-cine MRI) to allow breath-hold acquisition, and we compared intracranial hemo- and hydrodynamic parameters obtained during breath holding between full inspiration and end expiration. On a 3.0 T MRI, using electrocardiogram (ECG)-synchronized fast PC-cine MRI with parallel imaging, rectangular field of view, and segmented k-space, we obtained velocity-mapped phase images at the mid-C2 level with different velocity encoding for transcranial blood flow and cerebrospinal-fluid (CSF) flow. Next, we calculated the peak-to-peak amplitudes of cerebral blood flow (ΔCBF), cerebral venous outflow, intracranial volume change, CSF pressure gradient (ΔPG), and intracranial compliance index. These parameters were compared between the proposed and conventional methods. Moreover, we compared these parameters between different utilized breath-hold maneuvers (inspiration, expiration, and free breathing). All parameters derived from the fast PC method agreed with those from the conventional method. The ΔPG was significantly higher during full inspiration breath holding than at the end of expiration and during free breathing. The proposed fast PC-cine MRI reduced scan time (within 30 s) with good agreement with conventional methods. The use of this method also makes it possible to assess the effects of respiration on intracranial hemo- and hydrodynamics.
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40
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Alaia EF, Subhas N. Shoulder MR Imaging and MR Arthrography Techniques: New Advances. Magn Reson Imaging Clin N Am 2020; 28:153-163. [PMID: 32241655 DOI: 10.1016/j.mric.2019.12.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
MR imaging is the standard diagnostic modality that provides a comprehensive and accurate assessment for both osseous and soft-tissue pathologic conditions of the shoulder. This article discusses standard MR imaging and arthrography protocols used routinely in clinical practice, as well as more innovative sequences and reconstruction techniques, facilitated by the increasing availability of high-field-strength magnets and multichannel phased array surface coils and incorporation of artificial intelligence. These exciting innovations allow for a more detailed and diagnostic imaging assessment, improvements in image quality, and more rapid image acquisition.
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Affiliation(s)
- Erin F Alaia
- Department of Radiology, Musculoskeletal Division, NYU Langone Health, NYU Langone Orthopedic Hospital, 301 East 17th Street, 6th Floor, New York, NY 10003, USA.
| | - Naveen Subhas
- Department of Radiology, Musculoskeletal Division, Imaging Institute, Cleveland Clinic, 9500 Euclid Avenue, A21, Cleveland, OH 44195, USA
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41
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Ferrer CJ, Bartels LW, van der Velden TA, Grüll H, Heijman E, Moonen CTW, Bos C. Field drift correction of proton resonance frequency shift temperature mapping with multichannel fast alternating nonselective free induction decay readouts. Magn Reson Med 2020; 83:962-973. [PMID: 31544289 PMCID: PMC6899537 DOI: 10.1002/mrm.27985] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 08/14/2019] [Accepted: 08/15/2019] [Indexed: 01/07/2023]
Abstract
PURPOSE To demonstrate that proton resonance frequency shift MR thermometry (PRFS-MRT) acquisition with nonselective free induction decay (FID), combined with coil sensitivity profiles, allows spatially resolved B0 drift-corrected thermometry. METHODS Phantom experiments were performed at 1.5T and 3T. Acquisition of PRFS-MRT and FID were performed during MR-guided high-intensity focused ultrasound heating. The phase of the FIDs was used to estimate the change in angular frequency δωdrift per coil element. Two correction methods were investigated: (1) using the average δωdrift over all coil elements (0th-order) and (2) using coil sensitivity profiles for spatially resolved correction. Optical probes were used for independent temperature verification. In-vivo feasibility of the methods was evaluated in the leg of 1 healthy volunteer at 1.5T. RESULTS In 30 minutes, B0 drift led to an apparent temperature change of up to -18°C and -98°C at 1.5T and 3T, respectively. In the sonicated area, both corrections had a median error of 0.19°C at 1.5T and -0.54°C at 3T. At 1.5T, the measured median error with respect to the optical probe was -1.28°C with the 0th-order correction and improved to 0.43°C with the spatially resolved correction. In vivo, without correction the spatiotemporal median of the apparent temperature was at -4.3°C and interquartile range (IQR) of 9.31°C. The 0th-order correction had a median of 0.75°C and IQR of 0.96°C. The spatially resolved method had the lowest median at 0.33°C and IQR of 0.80°C. CONCLUSION FID phase information from individual receive coil elements allows spatially resolved B0 drift correction in PRFS-based MRT.
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Affiliation(s)
- Cyril J. Ferrer
- Imaging DivisionUniversity Medical Center UtrechtUtrechtNetherlands
| | | | | | - Holger Grüll
- Faculty of Medicine and University Hospital of CologneDepartment of Diagnostic and Interventional RadiologyUniversity of CologneCologneGermany
| | - Edwin Heijman
- Faculty of Medicine and University Hospital of CologneDepartment of Diagnostic and Interventional RadiologyUniversity of CologneCologneGermany
- Oncology SolutionsPhilips ResearchAachenGermany
| | | | - Clemens Bos
- Imaging DivisionUniversity Medical Center UtrechtUtrechtNetherlands
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Kozak BM, Jaimes C, Kirsch J, Gee MS. MRI Techniques to Decrease Imaging Times in Children. Radiographics 2020; 40:485-502. [PMID: 32031912 DOI: 10.1148/rg.2020190112] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Long acquisition times can limit the use of MRI in pediatric patients, and the use of sedation or general anesthesia is frequently necessary to facilitate diagnostic examinations. The use of sedation or anesthesia has disadvantages including increased cost and imaging time and potential risks to the patient. Reductions in imaging time may decrease or eliminate the need for sedation or general anesthesia. Over the past decade, a number of imaging techniques that can decrease imaging time have become commercially available. These products have been used increasingly in clinical practice and include parallel imaging, simultaneous multisection imaging, radial k-space acquisition, compressed sensing MRI reconstruction, and automated protocol selection software. The underlying concepts, supporting data, current clinical applications, and available products for each of these strategies are reviewed in this article. In addition, emerging techniques that are still under investigation may provide further reductions in imaging time, including artificial intelligence-based reconstruction, gradient-controlled aliasing sampling and reconstruction, three-dimensional MR spectroscopy, and prospective motion correction. The preliminary results for these techniques are also discussed. ©RSNA, 2020 See discussion on this article by Greer and Vasanawala.
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Affiliation(s)
- Benjamin M Kozak
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Founders 210, Boston, MA 02114 (B.M.K., J.K., M.S.G.); Department of Radiology, Harvard Medical School, Boston, Mass (B.M.K., C.J., J.K., M.S.G.); and Department of Radiology, Boston Children's Hospital, Boston, Mass (C.J.)
| | - Camilo Jaimes
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Founders 210, Boston, MA 02114 (B.M.K., J.K., M.S.G.); Department of Radiology, Harvard Medical School, Boston, Mass (B.M.K., C.J., J.K., M.S.G.); and Department of Radiology, Boston Children's Hospital, Boston, Mass (C.J.)
| | - John Kirsch
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Founders 210, Boston, MA 02114 (B.M.K., J.K., M.S.G.); Department of Radiology, Harvard Medical School, Boston, Mass (B.M.K., C.J., J.K., M.S.G.); and Department of Radiology, Boston Children's Hospital, Boston, Mass (C.J.)
| | - Michael S Gee
- From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Founders 210, Boston, MA 02114 (B.M.K., J.K., M.S.G.); Department of Radiology, Harvard Medical School, Boston, Mass (B.M.K., C.J., J.K., M.S.G.); and Department of Radiology, Boston Children's Hospital, Boston, Mass (C.J.)
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43
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Newly Developed Methods for Reducing Motion Artifacts in Pediatric Abdominal MRI: Tips and Pearls. AJR Am J Roentgenol 2020; 214:1042-1053. [PMID: 32023117 DOI: 10.2214/ajr.19.21987] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE. The purpose of this article is to review established and emerging methods for reducing motion artifacts in pediatric abdominal MRI. CONCLUSION. Clearly understanding the strengths and limitations of motion reduction methods can enable practitioners of pediatric abdominal MRI to select and combine the appropriate techniques and potentially reduce the need for sedation and anesthesia.
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Chea P, Mandell JC. Current applications and future directions of deep learning in musculoskeletal radiology. Skeletal Radiol 2020; 49:183-197. [PMID: 31377836 DOI: 10.1007/s00256-019-03284-z] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 07/11/2019] [Accepted: 07/15/2019] [Indexed: 02/02/2023]
Abstract
Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, which can be conceptually divided into the categories of lesion detection, classification, segmentation, and non-interpretive tasks. Numerous examples of deep learning achieving expert-level performance in specific tasks in all four categories have been demonstrated in the past few years, although comprehensive interpretation of imaging examinations has not yet been achieved. It is important for the practicing musculoskeletal radiologist to understand the current scope of deep learning as it relates to musculoskeletal radiology. Interest in deep learning from researchers, radiology leadership, and industry continues to increase, and it is likely that these developments will impact the daily practice of musculoskeletal radiology in the near future.
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Affiliation(s)
- Pauley Chea
- Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Jacob C Mandell
- Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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45
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Nam JG, Lee JM, Lee SM, Kang HJ, Lee ES, Hur BY, Yoon JH, Kim E, Doneva M. High Acceleration Three-Dimensional T1-Weighted Dual Echo Dixon Hepatobiliary Phase Imaging Using Compressed Sensing-Sensitivity Encoding: Comparison of Image Quality and Solid Lesion Detectability with the Standard T1-Weighted Sequence. Korean J Radiol 2019; 20:438-448. [PMID: 30799575 PMCID: PMC6389821 DOI: 10.3348/kjr.2018.0310] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Accepted: 09/03/2018] [Indexed: 12/19/2022] Open
Abstract
Objective To compare a high acceleration three-dimensional (3D) T1-weighted gradient-recalled-echo (GRE) sequence using the combined compressed sensing (CS)-sensitivity encoding (SENSE) method with a conventional 3D GRE sequence using SENSE, with respect to image quality and detectability of solid focal liver lesions (FLLs) in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced liver MRI. Materials and Methods A total of 217 patients with gadoxetic acid-enhanced liver MRI at 3T (54 in the preliminary study and 163 in the main study) were retrospectively included. In the main study, HBP imaging was done twice using the standard mDixon-3D-GRE technique with SENSE (acceleration factor [AF]: 2.8, standard mDixon-GRE) and the high acceleration mDixon-3D GRE technique using the combined CS-SENSE technique (CS-SENSE mDixon-GRE). Two abdominal radiologists assessed the two MRI data sets for image quality in consensus. Three other abdominal radiologists independently assessed the diagnostic performance of each data set and its ability to detect solid FLLs in 117 patients with 193 solid nodules and compared them using jackknife alternative free-response receiver operating characteristics (JAFROC). Results There was no significant difference in the overall image quality. CS-SENSE mDixon-GRE showed higher image noise, but lesser motion artifact levels compared with the standard mDixon-GRE (all p < 0.05). In terms of lesion detection, reader-averaged figures-of-merit estimated with JAFROC was 0.918 for standard mDixon-GRE, and 0.953 for CS-SENSE mDixon-GRE (p = 0.142). The non-inferiority of CS-SENSE mDixon-GRE over standard mDixon-GRE was confirmed (difference: 0.064 [−0.012, 0.081]). Conclusion The CS-SENSE mDixon-GRE HBP sequence provided comparable overall image quality and non-inferior solid FFL detectability compared with the standard mDixon-GRE sequence, with reduced acquisition time.
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Affiliation(s)
- Ju Gang Nam
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.,Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.
| | - Sang Min Lee
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Hyo Jin Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Eun Sun Lee
- Department of Radiology, Chung-Ang University Hospital, Seoul, Korea
| | - Bo Yun Hur
- Department of Radiology, National Cancer Center, Goyang, Korea
| | - Jeong Hee Yoon
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - EunJu Kim
- Department of Clinical Science, MR, Philips Healthcare Korea, Seoul, Korea
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Obuchowicz R, Piórkowski A, Urbanik A, Strzelecki M. Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features. BIOMED RESEARCH INTERNATIONAL 2019; 2019:3706581. [PMID: 31828100 PMCID: PMC6886329 DOI: 10.1155/2019/3706581] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 08/06/2019] [Accepted: 09/01/2019] [Indexed: 12/21/2022]
Abstract
Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that has undergone controlled degradation by using textural features in the image. Images of 41 patients, 17 women and 24 men, aged between 23 and 56 years were analyzed. T2-weighted sagittal sequences of the lumbar spine, cervical spine, and knee and T2-weighted coronal sequences of the shoulder and wrist were generated. The implementation of parallel imaging with the use of GRAPPA2, GRAPPA3, and GRAPPA4 led to a substantial reduction in the scanning time but also degraded image quality. The number of degraded image textural features was correlated with the scanning time. Longer scan times correlated with markedly higher ITF image persistence in comparison with images computed with reduced scan times. Higher ITF preservation was observed in images of bones in the spine and femur as compared to images of soft tissues, i.e., tendons and muscles. Finally, a nonparametrized image quality assessment based on an analysis of the ITF, computed for different tissues, correlating with the changes in acquisition time of the MR images, was successfully developed. The correlation between acquisition time and the number of reproducible features present in an MR image was found to yield the necessary assumptions to calculate the quality index.
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Affiliation(s)
- Rafał Obuchowicz
- Department of Diagnostic Imaging, Jagiellonian University Medical College, Kraków 31-501, Poland
| | - Adam Piórkowski
- Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, Kraków 30-059, Poland
| | - Andrzej Urbanik
- Department of Diagnostic Imaging, Jagiellonian University Medical College, Kraków 31-501, Poland
| | - Michał Strzelecki
- Institute of Electronics, Łódź University of Technology, Łódź 90-924, Poland
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Timilsina R, Qian C. Parallel magnetic resonance image reconstruction from a single-element parametric amplifier. Magn Reson Imaging 2019; 63:147-154. [PMID: 31425798 PMCID: PMC6861694 DOI: 10.1016/j.mri.2019.08.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 07/22/2019] [Accepted: 08/15/2019] [Indexed: 11/30/2022]
Abstract
In magnetic resonance imaging (MRI), acquisition speed is always an important issue. In this paper, we propose a promising technique to achieve parallel MRI (pMRI) on a single-channel spectrometer, using a novel Wireless Amplified Nuclear MR Detector (WAND) for spatial encoding in image reconstruction. For this, a planar structure double frequency WAND is designed and fabricated, where two of its frequencies - 'signal', ω1 and 'idler', ω2 are effectively utilized as two separate "channels" for accelerated acquisition. We provided a thorough background needed for the method and subsequently parallel imaging algorithms. Sum-of-Squares (SoS) reconstruction and GeneRalized Autocalibrating Partially Parallel Acquisition (GRAPPA) reconstruction are used to reconstruct as well as to analyze the SNR in the resulting images and validate our hypothesis. Experimental results using phantom datasets demonstrate that the proposed method of parallel imaging yield a better sensitivity for the combined images ('idler' + 'signal') than the sensitivity acquired for each individual image and thus significantly improving the reconstruction quality with optimal signal-to-noise ratio. We also demonstrated the achievable acceleration factor of this approach.
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Affiliation(s)
- Roshan Timilsina
- Department of Physics, Oakland University, Rochester, MI 48309, USA; Department of Radiology, Michigan State University, East Lansing, MI 48824, USA
| | - Chunqi Qian
- Department of Physics, Oakland University, Rochester, MI 48309, USA; Department of Radiology, Michigan State University, East Lansing, MI 48824, USA.
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Kapur S, Jana M, Gupta L, Bhalla AS, Naranje P, Gupta AK. Chest MRI Using Multivane-XD, a Novel T2-Weighted Free Breathing MR Sequence. Curr Probl Diagn Radiol 2019; 50:41-47. [PMID: 31383474 DOI: 10.1067/j.cpradiol.2019.07.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 07/04/2019] [Accepted: 07/08/2019] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To compare image quality of free-breathing T2-weighted MultiVane-XD (MVXD) sequence (non-Cartesian k-space filling using radial rectangular blades) with conventional MR sequences (short tau inversion recovery [STIR],balanced true field echo [BTFE], T1 in phase fast field echo [T1 FFE], and T1-fat saturated postgadolinium [T1PG]) in MR imaging of chest. MATERIALS AND METHODS Twenty-one patients (10 men and 11 women) underwent chest MRI including T2W MVXD, STIR, BTFE (18/21), T1 FFE, T1PG (10/21) sequences at 1.5 T. Two reviewers (A.S.B and M.J. with 20 and 10 years of experience in pulmonary imaging, respectively) evaluated each sequence with respect to overall image quality, image sharpness, definition of mediastinal vessels including the aorta, pulmonary arteries, superior vena cava, intrapulmonary vessels; trachea, main bronchi, intrapulmonary airways; lung-mediastinal interface, pulmonary lesion detection, and artefacts in the upper, middle, and lower third of chest using 5-point scales. No sedation was given. Pairwise comparisons between T2W MVXD and the 4 conventional sequences were made using unpaired student's t test. RESULTS Mean age of patients was 30.67 years (range: 6-60 years). T2 MVXD showed significantly better overall image quality and sharpness than STIR, T1 FFE, and T1PG (P < 0.01) while it was comparable to BTFE. Mediastinal vessels were significantly better visualized on T2 MVXD as compared to STIR and T1 (P < 0.003). However, BTFE and T1PG were superior to T2 MVXD for visualization of great vessels, SVC, and intrapulmonary vessels (P < 0.01). Visualization of trachea, major bronchi, intrapulmonary airways as well as intrapulmonary lesion detection was significantly better on T2 MVXD images in comparison to any of the other 4 sequences (P < 0.03). Intrapulmonary artifacts were significantly lesser in BTFE images as compared to T2 MVXD (P < 0.01). No significant difference was found between the severity of intrapulmonary artifacts in other MR sequences as compared to T2 MVXD. CONCLUSIONS By virtue of its better overall image quality, sharpness, superior visualization of mediastinal airways, and lesion detection, T2 MultiVane-XD promises to be a robust addition in the armamentarium of thoracic radiologists.
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Affiliation(s)
- Savinay Kapur
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Manisha Jana
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Lalit Gupta
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Ashu S Bhalla
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India.
| | - Priyanka Naranje
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Arun K Gupta
- Department of Radiodiagnosis, All India Institute of Medical Sciences, New Delhi 110029, India
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Kaniewska M, de Beus JM, Ahlhelm F, Mameghani A, Eid K, Kubik-Huch RA, Anderson SE. Whole spine localizers of magnetic resonance imaging detect unexpected vertebral fractures. Acta Radiol 2019; 60:742-748. [PMID: 30142998 DOI: 10.1177/0284185118796673] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Whole spine localizers (WS-loc) of magnetic resonance imaging (MRI) are performed for enumeration of the vertebrae but they can be also used for the evaluation of the spine. PURPOSE To assess the accuracy of fracture detection using WS-locs of MRI and compare the findings with standard high-resolution short tau inversion recovery (STIR) sequences, and to determine whether the review of WS-locs is useful and if additional information can be gained by assessing the thoracic spine section of the WS-locs. MATERIAL AND METHODS A total of 298 magnetic resonance (MR) examinations of the lumbar spine with WS-locs were evaluated. Two independent readers reviewed the images. In case of fracture detection, further characterization of the fracture was performed. To assess inter-reader agreement, unweighted Cohen's kappa with 95% confidence intervals (CI) and Phi coefficients were calculated. RESULTS The study sample included 187 female and 111 male patients (age range = 65-94 years; median age = 75.0 years). The WS-locs detected 42 fractures of the lumbar spine and 36 of the thoracic spine. Inter-reader agreement for fracture detection in the lumbar and thoracic spine was strong (K = 0.87, 95% CI = 0.78-0.95, Phi = 0.87, and K = 0.88, 95% CI = 0.79-0.96, Phi = 0.88, respectively). CONCLUSION WS-locs from MR examinations of the lumbar spine provide a good diagnostic tool for the detection and evaluation of unsuspected vertebral fractures. WS-locs show strong inter-reader agreement for fracture detection in the thoracic and lumbar spine.
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Affiliation(s)
| | | | - Frank Ahlhelm
- Institute of Radiology, Kantonsspital Baden, Baden, Switzerland
| | - Alexander Mameghani
- Centre for Orthopedic Surgery, Kantonsspital Aarau und Baden, Baden, Switzerland
| | - Karim Eid
- Centre for Orthopedic Surgery, Kantonsspital Aarau und Baden, Baden, Switzerland
| | | | - Suzanne E Anderson
- Institute of Radiology, Kantonsspital Baden, Baden, Switzerland
- The University of Notre Dame Australia, Sydney School of Medicine, Sydney, NSW, Australia
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50
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El Mendili MM, Querin G, Bede P, Pradat PF. Spinal Cord Imaging in Amyotrophic Lateral Sclerosis: Historical Concepts-Novel Techniques. Front Neurol 2019; 10:350. [PMID: 31031688 PMCID: PMC6474186 DOI: 10.3389/fneur.2019.00350] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 03/21/2019] [Indexed: 01/13/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease with no effective disease modifying therapies at present. Spinal cord degeneration is a hallmark feature of ALS, highlighted in the earliest descriptions of the disease by Lockhart Clarke and Jean-Martin Charcot. The anterior horns and corticospinal tracts are invariably affected in ALS, but up to recently it has been notoriously challenging to detect and characterize spinal pathology in vivo. With recent technological advances, spinal imaging now offers unique opportunities to appraise lower motor neuron degeneration, sensory involvement, metabolic alterations, and interneuron pathology in ALS. Quantitative spinal imaging in ALS has now been used in cross-sectional and longitudinal study designs, applied to presymptomatic mutation carriers, and utilized in machine learning applications. Despite its enormous clinical and academic potential, a number of physiological, technological, and methodological challenges limit the routine use of computational spinal imaging in ALS. In this review, we provide a comprehensive overview of emerging spinal cord imaging methods and discuss their advantages, drawbacks, and biomarker potential in clinical applications, clinical trial settings, monitoring, and prognostic roles.
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Affiliation(s)
- Mohamed Mounir El Mendili
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.,Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France
| | - Giorgia Querin
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
| | - Peter Bede
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France.,Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Pierre-François Pradat
- Biomedical Imaging Laboratory (LIB), Sorbonne University, CNRS, INSERM, Paris, France.,Department of Neurology, Pitié-Salpêtrière University Hospital (APHP), Paris, France
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