Purpose:Motion artifacts induced by breathing variations are common in 4D-MRI images.This study aims to reduce the motion artifacts by developing a novel,robust 4D-MRI sorting method based on anatomic feature matching...Purpose:Motion artifacts induced by breathing variations are common in 4D-MRI images.This study aims to reduce the motion artifacts by developing a novel,robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition.Method:The proposed method uses the diaphragm as the anatomic feature to guide the sorting of 4D-MRI images.Initially,both abdominal 2D sagittal cine MRI images and axial MRI images were acquired.The sagittal cine MRI images were divided into 10 phases as ground truth.Next,the phase of each axial MRI image is determined by matching its diaphragm position in the intersection plane to the ground truth cine MRI.Then,those matched phases axial images were sorted into 10-phase bins which were identical to the ground truth cine images.Finally,10-phase 4D-MRI were reconstructed from these sorted axial images.The accuracy of reconstructed 4D-MRI data was evaluated by comparing with the ground truth using the 4D eXtended Cardiac Torso(XCAT)digital phantom.The effects of breathing signal,including both regular(cosine function)and irregular(patient data)in both axial cine and sequential scanning modes,on reconstruction accuracy were investigated by calculating total relative error(TRE)of the 4D volumes,Volume-Percent-Difference(VPD)and Center-of-Mass-Shift(COMS)of the estimated tumor volume,compared with the ground truth XCAT images.Results:In both scanning modes,reconstructed 4D-MRI images matched well with ground truth with minimal motion artifacts.The averaged TRE of the 4D volume,VPD and COMS of the EOE phase in both scanning modes are 0.32%/1.20%/0.05 mm for regular breathing,and 1.13%/4.26%/0.21 mm for patient irregular breathing.Conclusion:The preliminary evaluation results illustrated the feasibility of the robust 4D-MRI sorting method based on anatomic feature matching.This method provides improved image quality with reduced motion artifacts for both cine and sequential scanning modes.展开更多
The clinical adaptation of 4D-MRI in respiratory motion management is limited by the low image quality and motion artifacts of 4D-MRI sequences.This study aims to develop a novel artifact Map-guided Nonlocal mean(AM-N...The clinical adaptation of 4D-MRI in respiratory motion management is limited by the low image quality and motion artifacts of 4D-MRI sequences.This study aims to develop a novel artifact Map-guided Nonlocal mean(AM-NLM)technique that can be integrated into the clinical 4D-MRI workflow to suppress motion artifacts and enhance image quality.The AM-NLM technique was developed and tested on 4D-MR images of 28 liver cancer patients.A multiphase motion field was computed on the frames with the minimum average localized gradient entropy for each phase to generate a full set of improved quality 4D-MR images.Artifact maps were calculated based on the local image sharpness to guide nonlocal averaging,and a set of denoised eight-phase 4D-MR images was finally generated.The 4D-MR images were evaluated for image quality and motion accuracy.Conventional 4D-MRI approaches were also evaluated for comparison.AM-NLM 4D-MR images have significant improvements in SNR and CNR compared to the original 4D-MR images.High motion accuracy was achieved for AM-NLM 4D-MR images because the average deviation in the diaphragm position from the mean value for each phase was at the subvoxel level.Both qualitative and quantitative results suggested that the 4D-MR images generated by the AM-NLM technique had high image quality while maintaining image sharpness and motion accuracy.The AM-NLM technique has shown capability of suppressing motion artifacts and enhancing image quality of clinically acquired 4D-MR images,making it a promising technique in applications of 4D-MRI in radiotherapy.展开更多
基金This research was partly supported by research grants(NIH R01 EB028324,NIH R01 CA226899,GRF 151021/18M,GRF 151022/19M and HMRF 06173276).
文摘Purpose:Motion artifacts induced by breathing variations are common in 4D-MRI images.This study aims to reduce the motion artifacts by developing a novel,robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition.Method:The proposed method uses the diaphragm as the anatomic feature to guide the sorting of 4D-MRI images.Initially,both abdominal 2D sagittal cine MRI images and axial MRI images were acquired.The sagittal cine MRI images were divided into 10 phases as ground truth.Next,the phase of each axial MRI image is determined by matching its diaphragm position in the intersection plane to the ground truth cine MRI.Then,those matched phases axial images were sorted into 10-phase bins which were identical to the ground truth cine images.Finally,10-phase 4D-MRI were reconstructed from these sorted axial images.The accuracy of reconstructed 4D-MRI data was evaluated by comparing with the ground truth using the 4D eXtended Cardiac Torso(XCAT)digital phantom.The effects of breathing signal,including both regular(cosine function)and irregular(patient data)in both axial cine and sequential scanning modes,on reconstruction accuracy were investigated by calculating total relative error(TRE)of the 4D volumes,Volume-Percent-Difference(VPD)and Center-of-Mass-Shift(COMS)of the estimated tumor volume,compared with the ground truth XCAT images.Results:In both scanning modes,reconstructed 4D-MRI images matched well with ground truth with minimal motion artifacts.The averaged TRE of the 4D volume,VPD and COMS of the EOE phase in both scanning modes are 0.32%/1.20%/0.05 mm for regular breathing,and 1.13%/4.26%/0.21 mm for patient irregular breathing.Conclusion:The preliminary evaluation results illustrated the feasibility of the robust 4D-MRI sorting method based on anatomic feature matching.This method provides improved image quality with reduced motion artifacts for both cine and sequential scanning modes.
文摘目的基于4D Flow MRI技术探究急性心肌梗死患者左心室(left ventricular,LV)腔内局部血流动能(kinetic energy,KE)改变。方法纳入30名急性心肌梗死(acute myocardial infarction,AMI)患者和20名对照者。应用4D Flow MRI技术定量评价左心室腔内血流动能,包括左心室平均动能、最小动能、收缩期动能、舒张期动能以及平面内动能(in-plane kinetic energy,In-plane KE)百分比。比较心肌梗死组和对照组之间以及梗死节段与非梗死节段之间血流动能参数的差异。结果与对照组相比,急性心肌梗死组左心室整体平均动能(10.7μJ/mL±3.3 vs 14.7μJ/mL±3.6,P<0.001)、收缩期动能(14.6μJ/mL±5.1 vs 18.9μJ/mL±3.9,P=0.003)及舒张期动能(7.9μJ/mL±2.5 vs 10.6μJ/mL±3.8,P=0.018)均显著降低,其中梗死节段较非梗死节段邻近心腔血流的平均动能降低而收缩期平面内动能百分比增加(49.5μJ/mL±18.7 vs 126.3μJ/mL±50.7,P<0.001;61.8%±11.5 vs 42.9%±14.4,P=0.001)。结论4D Flow MRI技术可定量评价左心室腔内局部血流动能参数。急性心肌梗死后整体心腔血流动能减低,而梗死节段邻近心腔局部血流平面内动能百分比增加。
基金the MR Imaging Unit at The University of Hong Kong for providing the research MRI scanning services.This work was partly supported by the General Research Fund(GRF)[grant numbers 15102118,15102219,15104323,and 15104822]the Uni-versity Grants Committee,Health and Medical Research Fund(HMRF)[grant numbers 06173276 and 10211606]+1 种基金the Health Bureau,Innova-tion and TechnologySupport Programme[grant number ITS/049/22FP]the NSFC Young Scientist Fund[grant number 82202941]from the People's Republic of China.
文摘The clinical adaptation of 4D-MRI in respiratory motion management is limited by the low image quality and motion artifacts of 4D-MRI sequences.This study aims to develop a novel artifact Map-guided Nonlocal mean(AM-NLM)technique that can be integrated into the clinical 4D-MRI workflow to suppress motion artifacts and enhance image quality.The AM-NLM technique was developed and tested on 4D-MR images of 28 liver cancer patients.A multiphase motion field was computed on the frames with the minimum average localized gradient entropy for each phase to generate a full set of improved quality 4D-MR images.Artifact maps were calculated based on the local image sharpness to guide nonlocal averaging,and a set of denoised eight-phase 4D-MR images was finally generated.The 4D-MR images were evaluated for image quality and motion accuracy.Conventional 4D-MRI approaches were also evaluated for comparison.AM-NLM 4D-MR images have significant improvements in SNR and CNR compared to the original 4D-MR images.High motion accuracy was achieved for AM-NLM 4D-MR images because the average deviation in the diaphragm position from the mean value for each phase was at the subvoxel level.Both qualitative and quantitative results suggested that the 4D-MR images generated by the AM-NLM technique had high image quality while maintaining image sharpness and motion accuracy.The AM-NLM technique has shown capability of suppressing motion artifacts and enhancing image quality of clinically acquired 4D-MR images,making it a promising technique in applications of 4D-MRI in radiotherapy.
