Objective:To explore the application value of CT measurement of renal depth correction, optimized acquisition and post-processing in the measurement of renal glomerular filtration rate (GFR) by Gates renal dynamic imaging.Methods:From January 2018 to November 2019, 157 patients (102 males, 55 females, age (51.4±14.5) years) including 118 in normal renal area group (adults with normal renal position and morphology, and excluding hydronephrosis, renal occupation, retroperitoneal mass and other factors affecting renal depth) and 39 in abnormal renal area group (19 of transplanted kidney, 11 of horseshoe kidney and 9 of ectopic kidney), were retrospectively enrolled in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. The GFR was measured by renal dynamic imaging Gates method. For the normal renal area group, the renal depth was calculated by CT method, the traditional Tonnesen formula or the Li Qian formula. For the abnormal renal area group, the GFR was measured by optimized acquisition and post-processing method (GFR optimization), the traditional post-processing method (GFR tradition), or Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula method (eGFR). The differences of the renal depth and corresponding GFR obtained by different methods were analyzed using one-way analysis of variance and the least significant difference (LSD) t test. The correlation was analyzed by Pearson correlation analysis, and the consistency was analyzed by Bland-Altman analysis. Results:In the normal renal area group, the left and right renal depth measured by CT were (7.40±1.43) and (7.51±1.37) cm. Tonnesen formula underestimated renal depth (left kidney: (6.03±0.82) cm, right kidney: (6.06±0.84) cm; F values: 64.145 and 68.567, both P<0.01), and the deviation increased with the increase of CT measured depth ( r values: 0.847 and 0.834, both P<0.01). The GFR measured by Tonnesen formula was (56.93±28.42) ml·min -1·1.73 m -2, and the difference was statistically significant compared with CT method ((73.43±36.56) ml·min -1·1.73 m -2; F=9.423, P<0.01). The renal left and right depth measured by Li Qian formula were (7.55±1.03) and (7.52±0.98) cm, and the total GFR was (73.65±34.50) ml·min -1·1.73 m -2 with no differences compared with CT method (all P>0.05). The GFR obtained by Li Qian formula had better correlation ( r=0.901, P<0.01) and consistency with CT method. In the abnormal renal area group, GFR optimization, GFR tradition and eGFR was (63.11±27.40), (48.40±25.45) and (59.89±32.24) ml·min -1·1.73 m -2, respectively, and the difference between GFR tradition and GFR optimization was statistically significant ( F=2.870, P=0.025). GFR optimization had better correlation ( r=0.941, P<0.01) and consistency with eGFR. Conclusions:Tonnesen formula underestimates the renal depth. Using CT to measure renal depth and perform depth correction can improve the accuracy of Gates method for GFR determination. For the special cases of transplanted kidney, horseshoe kidney, ectopic kidney and retroperitoneal mass, it is important to optimize acquisition scheme and post-processing method to obtain accurate GFR.

Objective:To evaluate the effects of different sphere volumes, target background ratio (T/B) and post-processing correction techniques on the quantitative results of 99Tc m SPECT/CT. Methods:Six spheres with different diameters (37, 28, 22, 17, 13, 10 mm) in National Electrical Manufacturers Association International Electrotechnical Commission (NEMA IEC) models were filled with a mixture of 0.54 MBq/ml 99Tc m and iodixanol. The mixture iodine content was about 0.3%(135 mg), which led to different T/B (32∶1, 16∶1, 8∶1, 4∶1) by changing the radioactivity concentration of the cylinder. Routine imaging was performed on different T/B phantoms which were scanned by SPECT/CT. The CT threshold method was used for the delineation of volume of interest (VOI). Then the same processing correction technique and ordered-subsets expectation maximization (OSEM) parameters were used to calculate the radioactivity concentrations of different spheres, and further compared with the true values, and the accuracies were calculated. Pearson correlation analysis was applied to evaluate the relationships between sphere volume, T/B and quantitative results. The sphere with T/B of 32∶1 and diameter of 37 mm were processed by 3 correction techniques (CT attenuation correction (CTAC)+ scatter correction (SC)+ resolution recovery (RR); CTAC+ SC; CTAC+ RR). One-way analysis of variance and the least significant difference t test were used to analyzed the effects of 3 correction techniques on the quantitative results and image contrasts. Results:There were significant relationships between the sphere volumes, T/B and the quantitative accuracy ( r values: 0.757, 0.409, both P<0.05). There were significant differences of 3 correction techniques on the quantitative results and image contrast ( F values: 139.665 and 38.905, both P<0.001). Among them, the quantitative error of CTAC+ SC+ RR was lower than that of CTAC+ SC ((9.63±8.82)% vs (38.89±2.17)%; P<0.001), and similar to that of CTAC+ RR ((8.70±6.64)%; P>0.05). The quantitative error of CTAC+ RR was lower than that of CTAC+ SC ( P<0.001). The image contrast of CTAC+ SC+ RR was higher than that of CTAC+ SC ((93.45±0.91)% vs (92.41±0.25)%; P<0.001) and the image contrast of CTAC+ SC was higher than that of CTAC+ RR ((91.37±0.87)%; P<0.001). Conclusions:The larger sphere volume and the higher T/B, the more quantitative accuracy. The volume has a more significant effect on quantitative accuracy than T/B. Choosing the appropriate correction technique is helpful to quantitative accuracy improvement. It is suggested to use CTAC+ SC+ RR in quantitative processing.

Objective To analyze the application effects of artificial intelligence (AI) software and Mimics software in preoperative three-dimensional (3D) reconstruction for thoracoscopic anatomical pulmonary segmentectomy. Methods A retrospective analysis was conducted on patients who underwent thoracoscopic pulmonary segmentectomy at the Second People's Hospital of Huai'an from October 2019 to March 2024. Patients who underwent AI 3D reconstruction were included in the AI group, those who underwent Mimics 3D reconstruction were included in the Mimics group, and those who did not undergo 3D reconstruction were included in the control group. Perioperative related indicators of each group were compared. Results A total of 168 patients were included, including 73 males and 95 females, aged 25-81 (61.61±10.55) years. There were 79 patients in the AI group, 53 patients in the Mimics group, and 36 patients in the control group. There were no statistical differences in gender, age, smoking history, nodule size, number of lymph node dissection groups, postoperative pathological results, or postoperative complications among the three groups (P>0.05). There were statistical differences in operation time (P<0.001), extubation time (P<0.001), drainage volume (P<0.001), bleeding volume (P<0.001), and postoperative hospital stay (P=0.001) among the three groups. There were no statistical differences in operation time, extubation time, bleeding volume, or postoperative hospital stay between the AI group and the Mimics group (P>0.05). There was no statistical difference in drainage volume between the AI group and the control group (P=0.494), while there were statistical differences in operation time, drainage tube retention time, bleeding volume, and postoperative hospital stay (P<0.05). Conclusion For patients requiring thoracoscopic anatomical pulmonary segmentectomy, preoperative 3D reconstruction and preoperative planning based on 3D images can shorten the operation time, postoperative extubation time and hospital stay, and reduce intraoperative bleeding and postoperative drainage volume compared with reading CT images only. The use of AI software for 3D reconstruction is not inferior to Mimics manual 3D reconstruction in terms of surgical guidance and postoperative recovery, which can reduce the workload of clinicians and is worth promoting.