Mohammadinejad Payam, Khandelwal Ashish, Inoue Akitoshi, Takahashi Hiroaki, Yalon Mariana, Long Zaiyang, Halaweish Ahmed F, Leng Shuai, Yu Lifeng, Lee Yong S, McCollough Cynthia H, Fletcher Joel G
Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
Siemens Medical Solutions USA, 40 Liberty Boulevard, Malvern, PA, 19355, USA.
Abdom Radiol (NY). 2022 Jun;47(6):2158-2167. doi: 10.1007/s00261-022-03475-8. Epub 2022 Mar 23.
To compare the utility of a novel metal artifact reduction algorithm to standard imaging in improving visualization of key structures, diagnostic confidence, and patient-level confidence in malignancy in patients with suspected bladder cancer.
Patients with hip implants undergoing CT urography for suspected bladder malignancy were enrolled. Images were reconstructed using 3 methods: (1) Filtered Back Projection (FBP), (2) Iterative Metal Artifact Reduction (iMAR), and (3) Adaptive Iterative Metal Artifact Reduction (AiMAR) strength 4. In multiple reading sessions, three radiologists graded visualization of critical anatomic structures and artifact severity (6-point scales, lower scores desirable), and diagnostic confidence in blinded fashion. They also graded patient-level confidence in malignancy based on imaging findings in each patient.
Thirty-two patients (8 females) with a mean age of 74.5 ± 8.5 years were included. The median (range) visualization scores for FBP, iMAR, and AiMAR were 3.6 (1.1-4.9), 1.6 (0.3-2.8), and 1.6 (0.3-2.6), respectively. Both iMAR and AiMAR had anatomic visualization and artifact scores better than FBP (P < 0.001 for both) and similar to each other (P > 0.05). Structures with the most improvement in visualization score with the use of metal artifact reduction algorithms included the obturator internus muscle, internal and external iliac nodal chains, and vagina. iMAR and AiMAR improved diagnostic confidence (P < 0.001) and patient-level confidence in malignancy (P ≤ 0.24).
For patients with hip prostheses and suspected bladder malignancy, the use of iMAR or AiMAR was shown to significantly reduce metal artifacts, thus improving diagnostic confidence and patient-level confidence in malignancy.
比较一种新型金属伪影减少算法与标准成像在改善疑似膀胱癌患者关键结构的可视化、诊断信心以及患者对恶性肿瘤的信心方面的效用。
纳入因疑似膀胱恶性肿瘤接受CT尿路造影的髋关节植入物患者。图像采用三种方法重建：（1）滤波反投影（FBP），（2）迭代金属伪影减少（iMAR），以及（3）自适应迭代金属伪影减少（AiMAR）强度4。在多次读片过程中，三名放射科医生以盲法对关键解剖结构的可视化和伪影严重程度（6分制，分数越低越好）以及诊断信心进行评分。他们还根据每位患者的影像学表现对患者对恶性肿瘤的信心进行评分。
纳入32例患者（8例女性），平均年龄74.5±8.5岁。FBP、iMAR和AiMAR的可视化评分中位数（范围）分别为3.6（1.1 - 4.9）、1.6（0.3 - 2.8）和1.6（0.3 - 2.6）。iMAR和AiMAR的解剖结构可视化和伪影评分均优于FBP（两者P均<0.001）且彼此相似（P>0.05）。使用金属伪影减少算法后可视化评分改善最大的结构包括闭孔内肌、髂内和髂外淋巴结链以及阴道。iMAR和AiMAR提高了诊断信心（P<0.001）以及患者对恶性肿瘤的信心（P≤0.24）。
对于有髋关节假体且疑似膀胱恶性肿瘤的患者，使用iMAR或AiMAR可显著减少金属伪影，从而提高诊断信心以及患者对恶性肿瘤的信心。
