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Nagata H, Ohno Y, Yoshikawa T, Yamamoto K, Shinohara M, Ikedo M, Yui M, Matsuyama T, Takahashi T, Bando S, Furuta M, Ueda T, Ozawa Y, Toyama H. Compressed sensing with deep learning reconstruction: Improving capability of gadolinium-EOB-enhanced 3D T1WI. Magn Reson Imaging 2024; 108:67-76. [PMID: 38309378 DOI: 10.1016/j.mri.2024.01.015] [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: 09/08/2023] [Revised: 01/20/2024] [Accepted: 01/26/2024] [Indexed: 02/05/2024]
Abstract
PURPOSE The purpose of this study was to determine the utility of compressed sensing (CS) with deep learning reconstruction (DLR) for improving spatial resolution, image quality and focal liver lesion detection on high-resolution contrast-enhanced T1-weighted imaging (HR-CE-T1WI) obtained by CS with DLR as compared with conventional CE-T1WI with parallel imaging (PI). METHODS Seventy-seven participants with focal liver lesions underwent conventional CE-T1WI with PI and HR-CE-T1WI, surgical resection, transarterial chemoembolization, and radiofrequency ablation, followed by histopathological or >2-year follow-up examinations in our hospital. Signal-to-noise ratios (SNRs) of liver, spleen and kidney were calculated for each patient, after which each SNR was compared by means of paired t-test. To compare focal lesion detection capabilities of the two methods, a 5-point visual scoring system was adopted for a per lesion basis analysis. Jackknife free-response receiver operating characteristic (JAFROC) analysis was then performed, while sensitivity and false positive rates (/data set) for consensus assessment of the two methods were also compared by using McNemar's test or the signed rank test. RESULTS Each SNR of HR-CE-T1WI was significantly higher than that of conventional CE-T1WI with PI (p < 0.05). Sensitivities for consensus assessment showed that HR-CE-MRI had significantly higher sensitivity than conventional CE-T1WI with PI (p = 0.004). Moreover, there were significantly fewer FP/cases for HR-CE-T1WI than for conventional CE-T1WI with PI (p = 0.04). CONCLUSION CS with DLR are useful for improving spatial resolution, image quality and focal liver lesion detection capability of Gd-EOB-DTPA enhanced 3D T1WI without any need for longer breath-holding time.
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Affiliation(s)
- Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Yoshiharu Ohno
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan; Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan.
| | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan; Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan; Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, 673-0021, Japan
| | - Kaori Yamamoto
- Canon Medical Systems Corporation, Otawara, Tochigi, 324-8550, Japan
| | - Maiko Shinohara
- Canon Medical Systems Corporation, Otawara, Tochigi, 324-8550, Japan
| | - Masato Ikedo
- Canon Medical Systems Corporation, Otawara, Tochigi, 324-8550, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Tochigi, 324-8550, Japan
| | - Takahiro Matsuyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Tomoki Takahashi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Shuji Bando
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Minami Furuta
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, 470-1192, Japan
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Ikeda H, Ohno Y, Yamamoto K, Murayama K, Ikedo M, Yui M, Kumazawa Y, Shimamura Y, Takagi Y, Nakagaki Y, Hanamatsu S, Obama Y, Ueda T, Nagata H, Ozawa Y, Iwase A, Toyama H. Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors. Cancers (Basel) 2024; 16:1714. [PMID: 38730665 PMCID: PMC11083776 DOI: 10.3390/cancers16091714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Diffusion-weighted images (DWI) obtained by echo-planar imaging (EPI) are frequently degraded by susceptibility artifacts. It has been suggested that DWI obtained by fast advanced spin-echo (FASE) or reconstructed with deep learning reconstruction (DLR) could be useful for image quality improvements. The purpose of this investigation using in vitro and in vivo studies was to determine the influence of sequence difference and of DLR for DWI on image quality, apparent diffusion coefficient (ADC) evaluation, and differentiation of malignant from benign head and neck tumors. METHODS For the in vitro study, a DWI phantom was scanned by FASE and EPI sequences and reconstructed with and without DLR. Each ADC within the phantom for each DWI was then assessed and correlated for each measured ADC and standard value by Spearman's rank correlation analysis. For the in vivo study, DWIs obtained by EPI and FASE sequences were also obtained for head and neck tumor patients. Signal-to-noise ratio (SNR) and ADC were then determined based on ROI measurements, while SNR of tumors and ADC were compared between all DWI data sets by means of Tukey's Honest Significant Difference test. RESULTS For the in vitro study, all correlations between measured ADC and standard reference were significant and excellent (0.92 ≤ ρ ≤ 0.99, p < 0.0001). For the in vivo study, the SNR of FASE with DLR was significantly higher than that of FASE without DLR (p = 0.02), while ADC values for benign and malignant tumors showed significant differences between each sequence with and without DLR (p < 0.05). CONCLUSION In comparison with EPI sequence, FASE sequence and DLR can improve image quality and distortion of DWIs without significantly influencing ADC measurements or differentiation capability of malignant from benign head and neck tumors.
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Affiliation(s)
- Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Kaori Yamamoto
- Canon Medical Systems Corporation, Otawara 324-8550, Tochigi, Japan
| | - Kazuhiro Murayama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Masato Ikedo
- Canon Medical Systems Corporation, Otawara 324-8550, Tochigi, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara 324-8550, Tochigi, Japan
| | - Yunosuke Kumazawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yurika Shimamura
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yui Takagi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yuhei Nakagaki
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yuki Obama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital, Toyoake 470-1192, Aichi, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
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Chen R, Luo R, Xu Y, Ou J, Li X, Yang Y, Cao L, Wu Z, Luo W, Liu H. Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding. J Magn Reson Imaging 2024. [PMID: 38587265 DOI: 10.1002/jmri.29383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 03/23/2024] [Accepted: 03/25/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues. PURPOSE To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI. STUDY TYPE Prospective. POPULATION Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis). FIELD STRENGTH/SEQUENCE 3-T, M2C EPICS DWI, and M2C DWI. ASSESSMENT The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated usingaSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale. STATISTICAL TESTS Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05. RESULTS In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts. DATA CONCLUSION Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rui Chen
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Ruohong Luo
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yongzhou Xu
- Department of MSC Clinical & Technical Solutions, Philips Healthcare, Shenzhen, China
| | - Jiehao Ou
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Xiaodan Li
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Yuelong Yang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Liqi Cao
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Zhigang Wu
- Department of MSC Clinical & Technical Solutions, Philips Healthcare, Shenzhen, China
| | - Wei Luo
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Hui Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
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Hu SX, Xiao Y, Peng WL, Zeng W, Zhang Y, Zhang XY, Ling CT, Li HX, Xia CC, Li ZL. Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing. Eur Radiol 2024; 34:842-851. [PMID: 37606664 DOI: 10.1007/s00330-023-09996-0] [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: 01/23/2023] [Revised: 04/20/2023] [Accepted: 06/02/2023] [Indexed: 08/23/2023]
Abstract
OBJECTIVES To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus. METHODS Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients. RESULTS DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05). CONCLUSIONS In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x. CLINICAL RELEVANCE STATEMENT Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice. KEY POINTS •Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.
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Affiliation(s)
- Si-Xian Hu
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Yi Xiao
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Wan-Lin Peng
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Wen Zeng
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Yu Zhang
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
| | - Xiao-Yong Zhang
- Clinical Science, Philips Healthcare, Chengdu, Sichuan, China
| | - Chun-Tang Ling
- Clinical Science, Philips Healthcare, Chengdu, Sichuan, China
| | - Hai-Xia Li
- C&TS, Philips Healthcare, Guangzhou, Guangdong, China
| | - Chun-Chao Xia
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
| | - Zhen-Lin Li
- Department of Radiology, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
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Furuta M, Ikeda H, Hanamatsu S, Yamamoto K, Shinohara M, Ikedo M, Yui M, Nagata H, Nomura M, Ueda T, Ozawa Y, Toyama H, Ohno Y. Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies. Eur J Radiol 2024; 171:111289. [PMID: 38237523 DOI: 10.1016/j.ejrad.2024.111289] [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: 10/07/2023] [Revised: 12/13/2023] [Accepted: 01/02/2024] [Indexed: 02/10/2024]
Abstract
PURPOSE The purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI). METHODS Forty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student's t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student's t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar's test. RESULTS DR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05). CONCLUSION RDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.
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Affiliation(s)
- Minami Furuta
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Kaori Yamamoto
- Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | | | - Masato Ikedo
- Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Tochigi, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Masahiko Nomura
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Yoshiharu Ohno
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
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Takenaka D, Ozawa Y, Yamamoto K, Shinohara M, Ikedo M, Yui M, Oshima Y, Hamabuchi N, Nagata H, Ueda T, Ikeda H, Iwase A, Yoshikawa T, Toyama H, Ohno Y. Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients. Magn Reson Med Sci 2023:mp.2023-0068. [PMID: 37661425 DOI: 10.2463/mrms.mp.2023-0068] [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: 09/05/2023] Open
Abstract
PURPOSE Deep learning reconstruction (DLR) has been recommended as useful for improving image quality. Moreover, compressed sensing (CS) or DLR has been proposed as useful for improving temporal resolution and image quality on MR sequences in different body fields. However, there have been no reports regarding the utility of DLR for image quality and T-factor assessment improvements on T2-weighted imaging (T2WI), short inversion time (TI) inversion recovery (STIR) imaging, and unenhanced- and contrast-enhanced (CE) 3D fast spoiled gradient echo (GRE) imaging with and without CS in comparison with thin-section multidetector-row CT (MDCT) for non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine the utility of DLR for improving image quality and the appropriate sequence for T-category assessment for NSCLC patients. METHODS As subjects for this study, 213 pathologically diagnosed NSCLC patients who underwent thin-section MDCT and MR imaging as well as T-factor diagnosis were retrospectively enrolled. SNR of each tumor was calculated and compared by paired t-test for each sequence with and without DLR. T-factor for each patient was assessed with thin-section MDCT and all MR sequences, and the accuracy for T-factor diagnosis was compared among all sequences and thin-section CT by means of McNemar's test. RESULTS SNRs of T2WI, STIR imaging, unenhanced thin-section Quick 3D imaging, and CE-thin-section Quick 3D imaging with DLR were significantly higher than SNRs of those without DLR (P < 0.05). Diagnostic accuracy of STIR imaging and CE-thick- or thin-section Quick 3D imaging was significantly higher than that of thin-section CT, T2WI, and unenhanced thick- or thin-section Quick 3D imaging (P < 0.05). CONCLUSION DLR is thus considered useful for image quality improvement on MR imaging. STIR imaging and CE-Quick 3D imaging with or without CS were validated as appropriate MR sequences for T-factor evaluation in NSCLC patients.
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Affiliation(s)
- Daisuke Takenaka
- Department of Radiology, Fujita Health University School of Medicine
- Department of Diagnostic Radiology, Hyogo Cancer Center
| | - Yoshiyuki Ozawa
- Department of Radiology, Fujita Health University School of Medicine
| | | | | | | | | | - Yuka Oshima
- Department of Radiology, Fujita Health University School of Medicine
| | - Nayu Hamabuchi
- Department of Radiology, Fujita Health University School of Medicine
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital
| | - Takeshi Yoshikawa
- Department of Radiology, Fujita Health University School of Medicine
- Department of Diagnostic Radiology, Hyogo Cancer Center
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine
| | - Yoshiharu Ohno
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
- Department of Diagnostic Radiology, Fujita Health University School of Medicine
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Seo M, Yoon J, Choi Y, Nickel D, Jang J, Shin NY, Ahn KJ, Kim BS. Image Quality of High-Resolution 3-Dimensional Neck MRI Using CAIPIRINHA-VIBE and GRASP-VIBE: An Intraindividual Comparative Study. Invest Radiol 2022; 57:711-719. [PMID: 35703461 DOI: 10.1097/rli.0000000000000886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Acquiring high-quality magnetic resonance imaging (MRI) of the head and neck region is often challenging due to motion and susceptibility artifacts. This study aimed to compare image quality of 2 high-resolution three-dimensional (3D) MRI sequences of the neck, controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), and golden-angle radial sparse parallel imaging (GRASP)-VIBE. MATERIALS AND METHODS One hundred seventy-three patients indicated for contrast-enhanced neck MRI examination were scanned using 3 T scanners and both CAIPIRINHA-VIBE and GRASP-VIBE with nearly isotropic 3D acquisitions (<1 mm in-plane resolution with analogous acquisition times). Patients' MRI scans were independently rated by 2 radiologists using a 5-grade Likert scale for overall image quality, artifact level, mucosal and lesion conspicuity, and fat suppression degree at separate anatomical regions. Interobserver agreement was calculated using the Cohen κ coefficient. The quality ratings of both sequences were compared using the Mann-Whitney U test. Nonuniformity and contrast-to-noise ratio values were measured in all subjects. Separate MRI scans were performed twice for each sequence in a phantom and healthy volunteer without contrast injection to calculate the signal-to-noise ratio (SNR). RESULTS The scores of overall image quality, overall artifact level, motion artifact level, and conspicuity of the nasopharynx, oropharynx, oral cavity, hypopharynx, and larynx were all significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE (all P 's < 0.001). Moderate to substantial interobserver agreement was observed in overall image quality (GRASP-VIBE κ = 0.43; CAIPIRINHA-VIBE κ = 0.59) and motion artifact level (GRASP-VIBE κ = 0.51; CAIPIRINHA-VIBE κ = 0.65). Lesion conspicuity was significantly higher in GRASP-VIBE than in CAIPIRINHA-VIBE ( P = 0.005). The degree of fat suppression was weaker in the lower neck regions in GRASP-VIBE (3.90 ± 0.72) than in CAIPIRINHA-VIBE (4.97 ± 0.21) ( P < 0.001). The contrast-to-noise ratio at hypopharyngeal level was significantly higher in GRASP-VIBE (6.28 ± 4.77) than in CAIPIRINHA-VIBE (3.14 ± 9.95) ( P < 0.001). In the phantom study, the SNR of GRASP-VIBE was 12 times greater than that of CAIPIRINHA-VIBE. The in vivo SNR of the volunteer MRI scan was 13.6 in CAIPIRINHA-VIBE and 20.7 in GRASP-VIBE. CONCLUSIONS Both sequences rendered excellent images for head and neck MRI scans. GRASP-VIBE provided better image quality, as well as mucosal and lesion conspicuities, with less motion artifacts, whereas CAIPIRINHA-VIBE provided better fat suppression in the lower neck regions.
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Affiliation(s)
- Minkook Seo
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Jimin Yoon
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Yangsean Choi
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Dominik Nickel
- Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | - Jinhee Jang
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Na-Young Shin
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Kook-Jin Ahn
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
| | - Bum-Soo Kim
- From the Department of Radiology, Seoul St Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, South Korea
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8
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Yoshida N, Nakaura T, Morita K, Yoneyama M, Tanoue S, Yokota Y, Uetani H, Nagayama Y, Kidoh M, Azuma M, Hirai T. Echo planar imaging with compressed sensitivity encoding (EPICS): Usefulness for head and neck diffusion-weighted MRI. Eur J Radiol 2022; 155:110489. [PMID: 36037584 DOI: 10.1016/j.ejrad.2022.110489] [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: 07/25/2021] [Revised: 04/05/2022] [Accepted: 08/02/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE To evaluate diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with compressed SENSE (EPICS) of the head and neck magnetic resonance imaging (MRI). METHOD We retrospectively observed 32 patients who underwent head and neck DWI according to either the conventional method (SENSE, reduction factor = 2), fast scanning method (SENSE, reduction factor = 4), or fast scanning method with EPICS (EPICS, reduction factor = 4). For quantitative analysis, contrast-to-noise-ratio (CNR), apparent diffusion coefficient (ADC) values, geometric distortion, and coefficient of variations (CV) were measured and compared. For qualitative analysis, all images were independently and blindly evaluated by two board-certified radiologists. RESULTS EPICS revealed the higher CNR between all location compared to those of SENSE with reduction factor = 4. Distortion in the anterior-posterior direction was significantly lower on EPICS than on the conventional scan (p = 0.02). A comparison between the ADC values of the EPICS and conventional scan revealed no significant differences. The CV was significantly lower for EPICS than the conventional scan [DWI: 0.22 (IQR: 0.15-0.30) vs 0.32 (IQR: 0.24-0.40), p = 0.02]. CONCLUSIONS Compressed SENSE combined with the high acceleration factor can improve image quality, homogeneity, and distortion in the head and neck DWI maintaining ADC values and the scan time duration.
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Affiliation(s)
- Naofumi Yoshida
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan.
| | - Kosuke Morita
- Department of Radiology, Kumamoto University Hospital, Japan
| | | | - Shota Tanoue
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Yasuhiro Yokota
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Hiroyuki Uetani
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Yasunori Nagayama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Masafumi Kidoh
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
| | - Minako Azuma
- Department of Radiology, Faculty of Medicine, University of Miyazaki, Japan
| | - Toshinori Hirai
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Japan
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Obama Y, Ohno Y, Yamamoto K, Ikedo M, Yui M, Hanamatsu S, Ueda T, Ikeda H, Murayama K, Toyama H. MR imaging for shoulder diseases: Effect of compressed sensing and deep learning reconstruction on examination time and imaging quality compared with that of parallel imaging. Magn Reson Imaging 2022; 94:56-63. [DOI: 10.1016/j.mri.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/03/2022] [Accepted: 08/02/2022] [Indexed: 11/29/2022]
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10
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Bunch PM, Sachs JR, Kelly HR, Lipford ME, West TG. Magnetic Resonance Imaging of Head and Neck Emergencies, a Symptom-Based Review, Part 1: General Considerations, Vision Loss, and Eye Pain. Magn Reson Imaging Clin N Am 2022; 30:409-424. [PMID: 35995470 DOI: 10.1016/j.mric.2022.04.005] [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] [Indexed: 11/30/2022]
Abstract
Use of magnetic resonance (MR) imaging in the emergency department continues to increase. Although computed tomography is the first-line imaging modality for most head and neck emergencies, MR is superior in some situations and imparts no ionizing radiation. This article provides a symptom-based approach to nontraumatic head and neck pathologic conditions most relevant to emergency head and neck MR imaging, emphasizing relevant anatomy, "do not miss" findings affecting clinical management, and features that may aid differentiation from potential mimics. Essential MR sequences and strategies for obtaining high-quality images when faced with patient motion and other technical challenges are also discussed.
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Affiliation(s)
- Paul M Bunch
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, USA.
| | - Jeffrey R Sachs
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, USA
| | - Hillary R Kelly
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Department of Radiology, Massachusetts Eye and Ear, 243 Charles Street, Boston, MA 02114, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02115, USA
| | - Megan E Lipford
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, USA
| | - Thomas G West
- Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, USA
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11
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Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer. Cancers (Basel) 2022; 14:cancers14123027. [PMID: 35740691 PMCID: PMC9220977 DOI: 10.3390/cancers14123027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/14/2022] [Accepted: 06/14/2022] [Indexed: 02/01/2023] Open
Abstract
Simple Summary Adaptive radiotherapy for head and neck cancer has become more routine due to an increase in imaging quality and improvement in radiation techniques. With the availability of faster adaptive workflows, it is possible to adapt more easily to (daily) changes. MRI offers besides great anatomical imaging, also functional information about the tumor and surrounding tissue. The aim of this review is to provide current state of evidence about target definition on MRI for adaptive strategies in the treatment of head and neck cancer. Abstract In recent years, MRI-guided radiotherapy (MRgRT) has taken an increasingly important position in image-guided radiotherapy (IGRT). Magnetic resonance imaging (MRI) offers superior soft tissue contrast in anatomical imaging compared to computed tomography (CT), but also provides functional and dynamic information with selected sequences. Due to these benefits, in current clinical practice, MRI is already used for target delineation and response assessment in patients with head and neck squamous cell carcinoma (HNSCC). Because of the close proximity of target areas and radiosensitive organs at risk (OARs) during HNSCC treatment, MRgRT could provide a more accurate treatment in which OARs receive less radiation dose. With the introduction of several new radiotherapy techniques (i.e., adaptive MRgRT, proton therapy, adaptive cone beam computed tomography (CBCT) RT, (daily) adaptive radiotherapy ensures radiation dose is accurately delivered to the target areas. With the integration of a daily adaptive workflow, interfraction changes have become visible, which allows regular and fast adaptation of target areas. In proton therapy, adaptation is even more important in order to obtain high quality dosimetry, due to its susceptibility for density differences in relation to the range uncertainty of the protons. The question is which adaptations during radiotherapy treatment are oncology safe and at the same time provide better sparing of OARs. For an optimal use of all these new tools there is an urgent need for an update of the target definitions in case of adaptive treatment for HNSCC. This review will provide current state of evidence regarding adaptive target definition using MR during radiotherapy for HNSCC. Additionally, future perspectives for adaptive MR-guided radiotherapy will be discussed.
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12
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Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN. Eur Radiol 2022; 32:6658-6667. [PMID: 35687136 DOI: 10.1007/s00330-022-08877-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 04/26/2022] [Accepted: 05/12/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To compare the utility of deep learning reconstruction (DLR) for improving acquisition time, image quality, and intraductal papillary mucinous neoplasm (IPMN) evaluation for 3D MRCP obtained with parallel imaging (PI), multiple k-space data acquisition for each repetition time (TR) technique (Fast 3D mode multiple: Fast 3Dm) and compressed sensing (CS) with PI. MATERIALS AND METHODS A total of 32 IPMN patients who had undergone 3D MRCPs obtained with PI, Fast 3Dm, and CS with PI and reconstructed with and without DLR were retrospectively included in this study. Acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) obtained with all protocols were compared using Tukey's HSD test. Results of endoscopic ultrasound, ERCP, surgery, or pathological examination were determined as standard reference, and distribution classifications were compared among all 3D MRCP protocols by McNemar's test. RESULTS Acquisition times of Fast 3Dm and CS with PI with and without DLR were significantly shorter than those of PI with and without DLR (p < 0.05). Each MRCP sequence with DLR showed significantly higher SNRs and CNRs than those without DLR (p < 0.05). IPMN distribution accuracy of PI with and without DLR and Fast 3Dm with DLR was significantly higher than that of Fast 3Dm without DLR and CS with PI without DLR (p < 0.05). CONCLUSION DLR is useful for improving image quality and IPMN evaluation capability on 3D MRCP obtained with PI, Fast 3Dm, or CS with PI. Moreover, Fast 3Dm and CS with PI may play as substitution to PI for MRCP in patients with IPMN. KEY POINTS • Mean examination times of multiple k-space data acquisitions for each TR and compressed sensing with parallel imaging were significantly shorter than that of parallel imaging (p < 0.0001). • When comparing image quality of 3D MRCPs with and without deep learning reconstruction, deep learning reconstruction significantly improved signal-to-noise ratio and contrast-to-noise ratio (p < 0.05). • IPMN distribution accuracies of parallel imaging with and without deep learning reconstruction (with vs. without: 88.0% vs. 88.0%) and multiple k-space data acquisitions for each TR with deep learning reconstruction (86.0%) were significantly higher than those of others (p < 0.05).
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13
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Qiu J, Liu J, Bi Z, Sun X, Gu Q, Hu G, Qin N. An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS). Skeletal Radiol 2022; 51:1273-1283. [PMID: 34854969 DOI: 10.1007/s00256-021-03954-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/01/2021] [Accepted: 11/01/2021] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To investigate the feasibility of compressed sensing MRI (CS-MRI) in the application of 2D spinal imaging and compare its performance with conventional MR imaging (non-CS-MRI). METHODS The CS imaging protocol was optimized on 5 volunteers. Non-CS-MRI and CS-MRI of 2D sagittal T1 weighted imaging (WI), Sag T2WI, and axial T2WI were performed for 71 patients (22 cervical, 8 thoracic, 41 lumbar MRI). Paired t tests were conducted to compare the total scan time. Three radiologists assessed image quality and lesion diagnosis independently. A Kendall W test was performed to assess interobserver agreement of the image quality scores and lesion diagnosis between readers. A nonparametric test (Wilcoxon test) was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreements were evaluated by kappa analysis. Paired t tests were conducted for SNR and CNR comparison. RESULTS The mean scan time for spine CS-MRI (4 min 28.7 s ± 34.6 s) was significantly shorter than that with non-CS-MRI (7 min 21.3 s ± 38.7 s, t = - 47.464, P < 0.0001). CS-MRI achieved higher SNR and CNR than Non-CS-MRI in image quality assessment. Interobserver agreements of lesion diagnosis were excellent between non-CS-MRI and CS-MRI (kappa value from 0.913 to 1.000, P < 0.001). Interstudy agreements of lesion assessments were also excellent (kappa value = 1.000, with P < 0.001). CONCLUSION CS-MRI spine imaging can significantly reduce the scan time, while maintaining comparable imaging quality to non-CS-MRI.
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Affiliation(s)
- Jianxing Qiu
- Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China
| | - Jing Liu
- Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China
| | - Zhongxu Bi
- Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China
| | - Xiaowei Sun
- Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China
| | | | - Geli Hu
- Philips Healthcare, Beijing, China
| | - Naishan Qin
- Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China.
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14
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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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15
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Hur SJ, Choi Y, Yoon J, Jang J, Shin NY, Ahn KJ, Kim BS. Intraindividual Comparison between the Contrast-Enhanced Golden-Angle Radial Sparse Parallel Sequence and the Conventional Fat-Suppressed Contrast-Enhanced T1-Weighted Spin-Echo Sequence for Head and Neck MRI. AJNR Am J Neuroradiol 2021; 42:2009-2015. [PMID: 34593379 DOI: 10.3174/ajnr.a7285] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 07/25/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The golden-angle radial sparse parallel-volumetric interpolated breath-hold (GRASP-VIBE) sequence is a recently introduced imaging technique with high resolution. This study compared the image quality between conventional fat-suppressed T1-weighted TSE and GRASP-VIBE after gadolinium enhancement in the head and neck region. MATERIALS AND METHODS Data from 65 patients with clinical indications for head and neck MR imaging between September 2020 and January 2021 were retrospectively reviewed. Two radiologists assessed the overall image quality, overall artifacts, and image conspicuities in the oropharynx, hypopharynx, and cervical lymph nodes according to 5-point scores (best score: 5). Interobserver agreement was assessed using weighted κ statistics. The SNR and contrast-to-noise ratio were calculated and compared between the 2 sequences using a paired Wilcoxon signed rank test. RESULTS The analysis included 52 patients (mean age, 60 [SD, 14 ] years; male, 71.2% [37/52]) who were mostly diagnosed with head and neck malignancies (94.3% [50/52]). κ statistics ranged from slight agreement in cervical lymph node conspicuity (κ = 0.18) to substantial agreement in oropharyngeal mucosal conspicuity (κ = 0.80) (κ range, 0.18-0.80). Moreover, GRASP-VIBE demonstrated significantly higher mean scores in overall image quality (4.68 [SD, 0.41] versus 3.66 [SD, 0.73]), artifacts (4.47 [SD, 0.48] versus 3.58 [SD, 0.71]), oropharyngeal mucosal conspicuity (4.85 [SD, 0.41] versus 4.11 [SD, 0.79]), hypopharyngeal mucosal conspicuity (4.84 [SD, 0.34] versus 3.58 [SD, 0.81]), and cervical lymph node conspicuity (4.79 [SD, 0.32] versus 4.08 [SD, 0.64]) than fat-suppressed T1-weighted TSE (all, P < .001). Furthermore, GRASP-VIBE demonstrated a higher SNR (22.8 [SD, 11.5] versus 11.3 [SD, 5.6], P < .001) and contrast-to-noise ratio (4.7 [SD, 5.4] versus 2.3 [SD, 2.7], P = .059) than fat-suppressed T1-weighted TSE. CONCLUSIONS GRASP-VIBE provided better image quality with fewer artifacts than conventional fat-suppressed T1-weighted TSE for the head and neck regions.
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Affiliation(s)
- S-J Hur
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Y Choi
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - J Yoon
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - J Jang
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - N-Y Shin
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - K-J Ahn
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - B-S Kim
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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