The saphenous veins (SV) are frequently employed as bypass grafts. The SV graft failure is predominantly seen at the valve site. Avoiding valves during vein harvest would help reduce graft failure. We endeavored to detect SV valves, tributaries, and vessel size employing upright CT for the raw cadaver venous samples and in healthy volunteers.Five cadaver legs were scanned. The anatomical analysis showed 3.0 (IQR: 2.0-3.0) valves and 13.50 (IQR: 10.00-16.25) tributaries. The upright CT completely detected, compared to 2.0 (IQR: 1.5-2.5, p=0.06) valves and 9.5 (IQR: 7.5-13.0, p=0.13) tributaries by supine CT. From a total 190 volunteers, 138 (men:75, women:63) were included. The number of valves from the SF junction to 35 cm were significantly higher in upright CT than in supine CT bilaterally [upright vs. supine, Right: 4 (IQR: 3-5) vs. 2 (IQR:1-2), p<0.0001, Left: 4 (IQR: 3-5) vs. 2 (IQR: 1-2), p <0.0001]. The number of tributaries and vessel area was also higher for upright compared with supine CT.Upright CT enable detection of SV valves, tributaries, and vessel size non-invasively. Although not tested here, it is expected that upright CT might potentially improve the graft assessment for bypass surgery.
Background: Narrowing of the acromiohumeral distance (AHD) implies a rotator cuff tear. However, conventional AHD measurements using two-dimensional (2D) imaging or with the patient in the supine position might differ from that while standing during daily activity. This study aimed to evaluate the three-dimensional (3D) actual distance between the acromion and humeral head in the standing position and compare the AHD values with those obtained using conventional measuring methods.Methods: Computed tomography (CT) images of 166 shoulders from 83 healthy volunteers (31 male and 52 female; mean age 40.1 ± 5.8 years; age range, 30–49 years) were prospectively acquired in the supine and standing positions using conventional and upright CT scanners, respectively. The minimum distance between the acromion and humeral head on the 3D surface models was considered as the 3D AHD. We measured the 2D AHD on anteroposterior digitally reconstructed radiographs. The AHD values were compared between the supine and standing positions and between the 2D and 3D measurements.Results: The mean values of 2D AHD were 8.8 ± 1.3 mm (range, 5.9–15.4 mm) in the standing position and 8.1 ± 1.2 mm (range, 5.3–14.3 mm) in the supine position. The mean values of 3D AHD were 7.3 ± 1.4 mm (range, 4.7–14.0 mm) in the standing position and 6.6 ± 1.2 mm (range, 4.4–13.7 mm) in the supine position. The values of 3D AHD were significantly lower than those of 2D AHDs in both the standing and supine positions (P < 0.001). The values of 2D and 3D AHDs were significantly lower in the supine position than in the standing position (P < 0.001). Conclusions: This study evaluated the 3D AHD of normal shoulders in the standing position using an upright CT scanner. The present results indicated that assessments in the supine position can underestimate the value of the AHD compared with those made in the standing position and that assessments using 2D analysis can overestimate the value.
The purpose of this study was to evaluate whether the prototype fine-cell detector computed tomography (FDCT) could improve smaller coronary artery stenosis measurement compared with 64-slice multidetector-row CT (MDCT). Method and Materials: We developed coronary phantoms of 2mm in diameter with 0%, 25%, 50%, 75% stenosis. Each stenotic part was made by Acrylonitrile-Butadiene-Styrene (ABS: 50 Hounsfield Unit (HU)) and lumen was filled with diluted iodine (380 HU). These coronary phantoms put into the water tank were scanned by both prototype FDCT and 64-slice MDCT. Configuration of FDCT was 32-row*0.3125mm detector collimation with 0.35mm smaller X-ray tube focal spot width, and that of 64-slice MDCT was 16-row*0.625mm detector collimation and 0.7mm X-ray focal spot. All axial images were reconstructed using Standard kernel with 96mm display field-of-view. Minimum lumen diameter and degree of stenosis in these data sets were automatically measured using the Vessel Analysis software (GE Healthcare). Results: Measured coronary lumen at 0%, 25%, 50%, 75% stenosis of 2mm-diameter phantom (corresponding to 2.0mm, 1.5mm, 1.0mm, 0.5mm) were 2.2mm, 1.8mm, 1.4mm, 0.7mm in FDCT, whereas those were 2.5mm, 2.0mm, 1.5mm, 1.4mm in 64-slice MDCT, respectively. Each degree of stenosis was calculated 21%, 38%, 69% in FDCT, while 20%, 38%, 44% in 64-slice MDCT. Measured value of 75% stenosis in FDCT was significantly improved compared with 64-slice MDCT. Conclusion: FDCT improves the accuracy of smaller coronary artery stenosis measurement compared with 64-slice MDCT. Superior spatial resolution of FDCT could be promising for more accurate assessment of the coronary artery stenosis.
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