Computed tomography (CT) based on the 3-dimensional reconstruction algorithm is vital for diagnosis, prognosis, and disease recurrence monitoring in non-muscle-invasive bladder cancer (NMIBC), according to a study published in Contrast Media & Molecular Imaging.

In this retrospective study, researchers analyzed 124 patients with NMIBC who underwent CT examination based on the 3-dimensional reconstruction algorithm before surgery. The study was separated into a case group (those receiving complete care) and a control group (those receiving conventional care). Researchers then compared the recovery status and recurrence of the 2 groups.

According to the results, accuracy, specificity, and sensitivity based on CT imaging via the 3-dimensional reconstruction algorithm were 89.38, 93.77, and 84.39, respectively. The researchers observed that the incidence of bladder spasm (9.68%), bladder flushing time (1.56 d), and retention of drainage tube time (2.68 d) were significantly lower in the case group compared with the control group (30.65%, 2.32 d, 5.19 d) (P<.05). Moreover, serum BLCA-1 (3.72 ng/mL) and CYFRA21-1 (5.68 μg/mL) were markedly lower than in the control group. The researchers found that role function (89.82 points), emotional function (84.76 points), somatic function (79.23 points), and social function (73.93 points) were higher in the case group (P<.05). Importantly, they also found that CT examination demonstrated that recurrence rate in the case group (6.45%) was notably lower than recurrence rate in the control group (22.58%) (P<.05).

CT detection based on the 3-dimensional reconstruction algorithm is important for preoperative diagnosis, prognosis, and recurrence monitoring of NMIBC patients, the investigators concluded.

Reference: Ke H, Qiu D, Cong Z. Prognosis analysis and perioperative research of elderly patients with non-muscle-invasive bladder cancer under computed tomography image of three-dimensional reconstruction algorithm. Contrast Media Mol Imaging. 2022;2022:6168528. doi:10.1155/2022/6168528

Link: https://pubmed.ncbi.nlm.nih.gov/35800229/