Objective To evaluate the image quality （IQ） and radiation dose of 128-slice dual-source computed tomography （DSCT） coronary angiography using prospectively electrocardiogram （ECG）-triggered sequen- tial scan mo...Objective To evaluate the image quality （IQ） and radiation dose of 128-slice dual-source computed tomography （DSCT） coronary angiography using prospectively electrocardiogram （ECG）-triggered sequen- tial scan mode compared with ECG-gated spiral scan mode in a population with atrial fibrillation. Methods Thirty-two patients with suspected coronary artery disease and permanent atrial fibrilla- tion referred for a second-generation 128-slice DSCT coronary angiography were included in the prospec- tive study. Of them, 17 patients （sequential group） were randomly selected to use a prospectively ECG.~triggered sequential scan, while the other 15 patients （spiral group） used a retrospectively ECG-gated spiral scan. The IQ was assessed by two readers independently, using a four-point grading scale from excel- lent （grade 1） to non-assessable （grade 4）, based on the American Heart Association 15-segment model. IQ of each segment and effective dose of each natient were comDared between the two groups. Results The mean heart rate （HR） of the sequential group was 96±27 beats per minute （bpm） with a variation range of 73±25 bpm, while the mean HR of the spiral group was 86±22 bpm with a variationrange of 65±24 bpm. Both of the mean FIR （t= 1.91, P=0.243） and HR variation range （t=0.950, P=0.350） had no significant difference between the two groups. In per-segment analysis, IQ of the sequential group vs. spiral group was rated as excellent （grade 1） in 190/244 （78%） vs. 177/217 （82%） by readerl and 197/245 （80%） vs. 174/214 （81%） by reader2, as non-assessable （grade 4） in 4/244 （2%） vs. 2/217 （1%） by readerl and 6/245 （2%） vs. 4/214 （2%） by reader2. Overall averaged IQ per-patient in the sequential and spiral group showed equally good （1.27＋0.19 vs. 1.25＋0.22, Z=-0.834, P=0.404）. The effective radiation dose of the sequential group reduced significantly compared with the spiral group （4.88±1.77 mSv vs. 10.20±3.64 mSv; t=-5.372, P=0.000）. Conclusion Compared with retrospectively ECG-gated spiral scan, prospectively ECG-triggered sequential DSCT coronary angiography provides similarly diagnostically valuable images in patients with atrial fibrillation and significantly reduces radiation dose.展开更多
The management of skeletal-related events(SREs),particularly the prevention of pathological fractures,is crucial for cancer patients.Current clinical assessment of fracture risk is mostly based on medical images,but i...The management of skeletal-related events(SREs),particularly the prevention of pathological fractures,is crucial for cancer patients.Current clinical assessment of fracture risk is mostly based on medical images,but incorporating sequential images in the assessment remains challenging.This study addressed this issue by leveraging a comprehensive dataset consisting of 260 longitudinal micro-computed tomography(μCT)scans acquired in normal and breast cancer bearing mice.A machine learning(ML)model based on a spatial–temporal neural network was built to forecast bone structures from previousμCT scans,which were found to have an overall similarity coefficient(Dice)of 0.814 with ground truths.Despite the predicted lesion volumes(18.5%±15.3%)being underestimated by~21%than the ground truths’(22.1%±14.8%),the time course of the lesion growth was better represented in the predicted images than the preceding scans(10.8%±6.5%).Under virtual biomechanical testing using finite element analysis(FEA),the predicted bone structures recapitulated the loading carrying behaviors of the ground truth structures with a positive correlation(y=0.863x)and a high coefficient of determination(R^(2)=0.955).Interestingly,the compliances of the predicted and ground truth structures demonstrated nearly identical linear relationships with the lesion volumes.In summary,we have demonstrated that bone deterioration could be proficiently predicted using machine learning in our preclinical dataset,suggesting the importance of large longitudinal clinical imaging datasets in fracture risk assessment for cancer bone metastasis.展开更多
文摘Objective To evaluate the image quality （IQ） and radiation dose of 128-slice dual-source computed tomography （DSCT） coronary angiography using prospectively electrocardiogram （ECG）-triggered sequen- tial scan mode compared with ECG-gated spiral scan mode in a population with atrial fibrillation. Methods Thirty-two patients with suspected coronary artery disease and permanent atrial fibrilla- tion referred for a second-generation 128-slice DSCT coronary angiography were included in the prospec- tive study. Of them, 17 patients （sequential group） were randomly selected to use a prospectively ECG.~triggered sequential scan, while the other 15 patients （spiral group） used a retrospectively ECG-gated spiral scan. The IQ was assessed by two readers independently, using a four-point grading scale from excel- lent （grade 1） to non-assessable （grade 4）, based on the American Heart Association 15-segment model. IQ of each segment and effective dose of each natient were comDared between the two groups. Results The mean heart rate （HR） of the sequential group was 96±27 beats per minute （bpm） with a variation range of 73±25 bpm, while the mean HR of the spiral group was 86±22 bpm with a variationrange of 65±24 bpm. Both of the mean FIR （t= 1.91, P=0.243） and HR variation range （t=0.950, P=0.350） had no significant difference between the two groups. In per-segment analysis, IQ of the sequential group vs. spiral group was rated as excellent （grade 1） in 190/244 （78%） vs. 177/217 （82%） by readerl and 197/245 （80%） vs. 174/214 （81%） by reader2, as non-assessable （grade 4） in 4/244 （2%） vs. 2/217 （1%） by readerl and 6/245 （2%） vs. 4/214 （2%） by reader2. Overall averaged IQ per-patient in the sequential and spiral group showed equally good （1.27＋0.19 vs. 1.25＋0.22, Z=-0.834, P=0.404）. The effective radiation dose of the sequential group reduced significantly compared with the spiral group （4.88±1.77 mSv vs. 10.20±3.64 mSv; t=-5.372, P=0.000）. Conclusion Compared with retrospectively ECG-gated spiral scan, prospectively ECG-triggered sequential DSCT coronary angiography provides similarly diagnostically valuable images in patients with atrial fibrillation and significantly reduces radiation dose.
基金partially supported by the Core Access Awards from the Delaware Center for Musculoskeletal Research funded by NIH COBRE(P20 GM139760)support from University of Delaware(Graduate Scholar Awards).
文摘The management of skeletal-related events(SREs),particularly the prevention of pathological fractures,is crucial for cancer patients.Current clinical assessment of fracture risk is mostly based on medical images,but incorporating sequential images in the assessment remains challenging.This study addressed this issue by leveraging a comprehensive dataset consisting of 260 longitudinal micro-computed tomography(μCT)scans acquired in normal and breast cancer bearing mice.A machine learning(ML)model based on a spatial–temporal neural network was built to forecast bone structures from previousμCT scans,which were found to have an overall similarity coefficient(Dice)of 0.814 with ground truths.Despite the predicted lesion volumes(18.5%±15.3%)being underestimated by~21%than the ground truths’(22.1%±14.8%),the time course of the lesion growth was better represented in the predicted images than the preceding scans(10.8%±6.5%).Under virtual biomechanical testing using finite element analysis(FEA),the predicted bone structures recapitulated the loading carrying behaviors of the ground truth structures with a positive correlation(y=0.863x)and a high coefficient of determination(R^(2)=0.955).Interestingly,the compliances of the predicted and ground truth structures demonstrated nearly identical linear relationships with the lesion volumes.In summary,we have demonstrated that bone deterioration could be proficiently predicted using machine learning in our preclinical dataset,suggesting the importance of large longitudinal clinical imaging datasets in fracture risk assessment for cancer bone metastasis.
