Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 m...Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.展开更多
Grating-based x-ray phase contrast imaging has attracted increasing interest in recent decades as multimodal and laboratory source usable method.Specific efforts have been focused on establishing a new extraction meth...Grating-based x-ray phase contrast imaging has attracted increasing interest in recent decades as multimodal and laboratory source usable method.Specific efforts have been focused on establishing a new extraction method to perform practical applications.In this work,noise properties of multi-combination information of newly established information extraction method,so-called angular signal radiography method,are investigated to provide guidelines for targeted and specific applications.The results show that how multi-combination of images can be used in targeted practical applications to obtain a high-quality image in terms of signal-to-noise ratio.Our conclusions can also hold true for upcoming targeted practical applications such as biomedical imaging,non-destructive imaging,and materials science.展开更多
目的探讨自主研发的16通道高分辨盆腔专用线圈(16C)在3.0 T盆腔MRI中的应用价值。材料和方法前瞻性招募35例行盆腔MRI的患者,分别用16C线圈和32通道的体部线圈(32C)采集相同的轴位和矢状位T2WI序列。比较相同序列图像中第三骶椎、子宫...目的探讨自主研发的16通道高分辨盆腔专用线圈(16C)在3.0 T盆腔MRI中的应用价值。材料和方法前瞻性招募35例行盆腔MRI的患者,分别用16C线圈和32通道的体部线圈(32C)采集相同的轴位和矢状位T2WI序列。比较相同序列图像中第三骶椎、子宫肌层、前列腺外周带、直肠壁和闭孔内肌的信噪比(signal to noise ratio,SNR)及对比噪声比(contrast to noise ratio,CNR)。由两位诊断医师各自对两组图像质量和直肠轴位图像直肠壁分层结构的显示度进行主观评分。结果两组线圈相同序列的T2WI矢状位第三骶椎、子宫肌层、前列腺外周带和轴位闭孔内肌的SNR差异具有统计学意义(P<0.05),矢状位第三骶椎、子宫肌层和轴位直肠壁对肌肉的CNR差异具有统计学意义(P<0.05),16C组高于32C组。两组线圈相同序列的T2WI图像质量主观评价差异具有统计学意义(P<0.05),16C组图像质量更优。在轴位T2WI直肠壁分层结构的显示度评价方面两组图像差异具有统计学意义(P<0.05),16C组更优。结论16C线圈在3.0 T磁共振设备上成像质量更好,更有利于盆腔疾病的诊断。展开更多
目的探究上腹部能谱CT智能匹配技术在提高图像对比噪声比(CNR)、降低对比剂使用量中的应用。方法选取行上腹部CT平扫以及双期增强扫描患者126例,分为实验组和对照组,各63例。实验组应用上腹部能谱CT智能匹配技术,对比剂含碘量为300 mg/...目的探究上腹部能谱CT智能匹配技术在提高图像对比噪声比(CNR)、降低对比剂使用量中的应用。方法选取行上腹部CT平扫以及双期增强扫描患者126例,分为实验组和对照组,各63例。实验组应用上腹部能谱CT智能匹配技术,对比剂含碘量为300 mg/kg,并采用滤波反投影法(FBP)获得A组图像;然后采用自适应统计迭代重组技术(AISR)获得B组图像。对照组采用常规CT平扫模式(120 k Vp),对比剂含碘量为450 mg/kg,采用FBP获得C组图像。比较三组图像在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像噪声以及肝、胰、门静脉、腹主动脉的CNR,并对三组图像进行评分。结果三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像噪声比较,差异均有统计学意义(F分别=187.72、246.35、51.98、127.50、23.15、48.96,P均<0.05)。两两比较结果显示,在40ke V动脉期和门静脉期,C组图像噪声低于B组和A组(q分别=8.32、9.37,P均<0.05);在50ke V动脉期和门静脉期时,B组和C组图像噪声均明显低于A组(q分别=5.73、6.84,P均<0.05);在60 ke V动脉期和门静脉期时,B组图像噪声均明显低于A组和C组(q分别=3.83、3.63,P均<0.05)。三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的肝、胰、腹主动脉(门静脉)CNR值比较,差异具有统计学意义(F分别=8.52、33.94、60.59、72.70、69.38、44.06;8.27、33.65、42.68、79.84、45.73、80.93;10.64、33.14、31.12、59.96、62.93、39.12,P均<0.05)。在40 ke V、50 ke V、60 ke V时,B组动脉期肝、胰、腹主动脉CNR值和门静脉期肝、胰、门静脉CNR值均明显高于A组和C组,差异均有统计学意义(q分别=16.73、8.72、12.71、10.82、14.65、15.71、11.67、12.51、8.77、10.52、9.79、13.80;8.79、12.83、10.62、14.62、10.81、8.51、10.66、12.79、13.72、9.81、10.53、12.49;4.49、5.64、6.82、10.53、7.52、5.93、11.61、9.27、6.31、10.65、9.51、10.11,P均<0.05)。三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像评分比较,差异均有统计学意义(F分别=42.58、77.97、18.30、25.04、4.25、5.14,P均<0.05)。两两比较结果显示,在40 ke V、50 ke V、60 ke V动脉期和门静脉期时,B组的图像评分最高,明显高于A组和C组(q分别=6.94、7.81、6.02、7.10;3.77、4.58、3.20、4.13;2.97、2.29、2.58、2.02,P均<0.05)。结论上腹部能谱CT智能匹配技术能够获得与常规CT平扫模式的对比剂用量,联合应用自适应统计迭代重组技术后,不仅能提高图像CNR以及降低对比剂用量,而且能提高图像质量。展开更多
文摘Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.
基金Project supported by the National Natural Science Foundation of China(Grant No.11535015)the National Special Foundation of China for Major Science Instrument(Grant No.61227802)+3 种基金the National Natural Science Foundation of China(Grant Nos.61405120,61605119,61571305,and 11674232)the Natural Science Foundation of Shenzhen,China(Grant No.JCYJ20170302142617703)the Natural Science Foundation of Shenzhen University,China(Grant Nos.2017017 and 2018041)sponsored by the Post-doctoral International Exchange Program of China
文摘Grating-based x-ray phase contrast imaging has attracted increasing interest in recent decades as multimodal and laboratory source usable method.Specific efforts have been focused on establishing a new extraction method to perform practical applications.In this work,noise properties of multi-combination information of newly established information extraction method,so-called angular signal radiography method,are investigated to provide guidelines for targeted and specific applications.The results show that how multi-combination of images can be used in targeted practical applications to obtain a high-quality image in terms of signal-to-noise ratio.Our conclusions can also hold true for upcoming targeted practical applications such as biomedical imaging,non-destructive imaging,and materials science.
文摘目的探讨自主研发的16通道高分辨盆腔专用线圈(16C)在3.0 T盆腔MRI中的应用价值。材料和方法前瞻性招募35例行盆腔MRI的患者,分别用16C线圈和32通道的体部线圈(32C)采集相同的轴位和矢状位T2WI序列。比较相同序列图像中第三骶椎、子宫肌层、前列腺外周带、直肠壁和闭孔内肌的信噪比(signal to noise ratio,SNR)及对比噪声比(contrast to noise ratio,CNR)。由两位诊断医师各自对两组图像质量和直肠轴位图像直肠壁分层结构的显示度进行主观评分。结果两组线圈相同序列的T2WI矢状位第三骶椎、子宫肌层、前列腺外周带和轴位闭孔内肌的SNR差异具有统计学意义(P<0.05),矢状位第三骶椎、子宫肌层和轴位直肠壁对肌肉的CNR差异具有统计学意义(P<0.05),16C组高于32C组。两组线圈相同序列的T2WI图像质量主观评价差异具有统计学意义(P<0.05),16C组图像质量更优。在轴位T2WI直肠壁分层结构的显示度评价方面两组图像差异具有统计学意义(P<0.05),16C组更优。结论16C线圈在3.0 T磁共振设备上成像质量更好,更有利于盆腔疾病的诊断。
文摘目的探究上腹部能谱CT智能匹配技术在提高图像对比噪声比(CNR)、降低对比剂使用量中的应用。方法选取行上腹部CT平扫以及双期增强扫描患者126例,分为实验组和对照组,各63例。实验组应用上腹部能谱CT智能匹配技术,对比剂含碘量为300 mg/kg,并采用滤波反投影法(FBP)获得A组图像;然后采用自适应统计迭代重组技术(AISR)获得B组图像。对照组采用常规CT平扫模式(120 k Vp),对比剂含碘量为450 mg/kg,采用FBP获得C组图像。比较三组图像在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像噪声以及肝、胰、门静脉、腹主动脉的CNR,并对三组图像进行评分。结果三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像噪声比较,差异均有统计学意义(F分别=187.72、246.35、51.98、127.50、23.15、48.96,P均<0.05)。两两比较结果显示,在40ke V动脉期和门静脉期,C组图像噪声低于B组和A组(q分别=8.32、9.37,P均<0.05);在50ke V动脉期和门静脉期时,B组和C组图像噪声均明显低于A组(q分别=5.73、6.84,P均<0.05);在60 ke V动脉期和门静脉期时,B组图像噪声均明显低于A组和C组(q分别=3.83、3.63,P均<0.05)。三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的肝、胰、腹主动脉(门静脉)CNR值比较,差异具有统计学意义(F分别=8.52、33.94、60.59、72.70、69.38、44.06;8.27、33.65、42.68、79.84、45.73、80.93;10.64、33.14、31.12、59.96、62.93、39.12,P均<0.05)。在40 ke V、50 ke V、60 ke V时,B组动脉期肝、胰、腹主动脉CNR值和门静脉期肝、胰、门静脉CNR值均明显高于A组和C组,差异均有统计学意义(q分别=16.73、8.72、12.71、10.82、14.65、15.71、11.67、12.51、8.77、10.52、9.79、13.80;8.79、12.83、10.62、14.62、10.81、8.51、10.66、12.79、13.72、9.81、10.53、12.49;4.49、5.64、6.82、10.53、7.52、5.93、11.61、9.27、6.31、10.65、9.51、10.11,P均<0.05)。三组在40 ke V、50 ke V、60 ke V动脉期和门静脉期的图像评分比较,差异均有统计学意义(F分别=42.58、77.97、18.30、25.04、4.25、5.14,P均<0.05)。两两比较结果显示,在40 ke V、50 ke V、60 ke V动脉期和门静脉期时,B组的图像评分最高,明显高于A组和C组(q分别=6.94、7.81、6.02、7.10;3.77、4.58、3.20、4.13;2.97、2.29、2.58、2.02,P均<0.05)。结论上腹部能谱CT智能匹配技术能够获得与常规CT平扫模式的对比剂用量,联合应用自适应统计迭代重组技术后,不仅能提高图像CNR以及降低对比剂用量,而且能提高图像质量。
文摘目的 探讨深度学习重建(deep learning reconstruction, DLR)技术对膀胱癌MRI图像质量及扫描时间的影响。材料与方法 前瞻性纳入病理诊断为膀胱癌的初诊患者分别行膀胱MRI常规快速自旋回波(fast-spin echo, FSE)-T2WI和DLR快速FSE-T2WI扫描,并保存未使用DLR的原始快速FSE-T2WI。由2名放射科医师分别对三组T2WI(常规FSE-T2WI、快速FSE-T2WI和DLR快速FSE-T2WI)的整体图像质量和图像伪影进行图像质量主观评价(5分标准)。由1名放射科医师测量病变的信噪比(signal-to-noise ratio, SNR)和病变与髂腰肌的对比噪声比(contrast-to-noise ratio, CNR)。对正态分布和非正态分布的数据分别进行单因素方差分析和Friedman检验,比较分析三组T2WI的主观评分和客观指标的差异。采用Weighted-Kappa检验比较组间及组内主观评分一致性。结果 本研究共纳入32例膀胱癌患者,年龄39~93(65±11)岁。缩短扫描时间的快速FSE-T2WI的整体图像质量、伪影评分、SNR(63.2±25.5 vs. 94.7±40.8,P<0.05)、CNR(40.0±19.0vs. 59.6±29.8,P<0.05)均显著低于常规FSE-T2WI;应用DLR显著提高快速FSE-T2WI的整体图像质量、伪影评分、SNR(256.7±102.9 vs. 63.2±25.5,P<0.05)、CNR(168.0±77.3 vs. 40.0±19.0,P<0.05);DLR快速FSE-T2WI的整体图像质量评分及SNR(256.7±102.9 vs. 94.7±40.8,P<0.05)和CNR(168.0±77.3 vs. 59.6±29.8,P<0.05)显著高于常规FSE-T2WI。结论 DLR可以缩短图像扫描时间,并在定量和定性方面提高图像质量,使膀胱癌患者更快完成MRI检查成为可能。
