OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

译文

目的。这项研究的目的是比较亚毫西弗胸部和腹盆腔CT的深度学习重建 (DLR) 和迭代重建 (IR) 图像的图像质量和临床上重要的病变检测。材料和方法。我们的前瞻性多机构研究包括59名成年患者 (33名女性,26名男性; 平均年龄 ± SD,65 ± 12岁; 平均体重指数 [体重 (公斤) 除以身高 (米) 的平方] = 27 ± 5),他们接受了常规胸部 (n = 22; 16名女性,六名男性) 和腹部骨盆 (n = 37; 17名女性,20名男性) 在640-MDCT扫描仪 (Aquilion ONE,佳能医疗系统) 上进行CT。所有患者均在临床指示的标准剂量 (SD) CT (SDCT) 后获得了低剂量 (LD) CT (LDCT) 的书面知情同意书。用交互式重建 (IR) (自适应迭代剂量减少 [AIDR] 3D,佳能医疗系统) 重建SDCT系列 (120 kVp,164-644 mA),用滤波反投影 (FBP) 重建LDCT (100 kVp,120 kVp; 30-50 mA),IR (AIDR 3D和基于正向投影模型的迭代重建解决方案 [第一],佳能医疗系统) 和深度学习重建 (DLR) (高级智能Clear-IQ引擎 [AiCE],佳能医疗系统)。四位经过专业培训的放射科医生首先读取所有LD图像集,然后以独立,随机和盲的方式将它们与SD AIDR 3D图像并排比较。亚专业放射科医生以3点比例评估LDCT图像的图像质量 (1 = 不可接受,2 = 次优,3 = 最佳)。获得描述性统计,并进行Wilcoxon符号秩检验。结果。LDCT的平均体积CT剂量指数和剂量长度乘积 (2.1 ± 0.8 mGy,49 ± 13mGy·cm) 低于SDCT的平均体积CT剂量指数和剂量长度乘积 (13 ± 4.4 mGy,567 ± 249 mGy·cm) (p <0.0001)。在SD AIDR 3D和LD DLR图像上观察到所有31个具有临床意义的腹部病变。在LD AIDR 3D,LD FIRST和LD FBP图像上分别检测到25、18和7个病变。在SD AIDR 3D图像上检测到的所有39个肺结节也在LD DLR图像上记录。LD DLR图像被认为可用于腹部97% (35/37) 和胸部LDCT研究的95-100% (21-22/22) 的解释 (p = 0.2-0.99)。LD FIRST、LD AIDR 3D和LD FBP图像与SD AIDR 3D图像相比具有较差的图像质量 (p <0.0001)。结论。在超毫西弗胸部和腹部盆腔CT剂量下,DLR使图像质量和病变检测优于商业IR和FBP图像。

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