Clinical study on improving diagnostic accuracy of focal prostate cancer based on 18F-PSMA-1007 PET/CT radiomics
- VernacularTitle:基于18F-PSMA-1007 PET/CT影像组学提高局灶性前列腺癌诊断准确性的临床研究
- Author:
Ruxi CHANG
1
;
Liang LUO
1
;
Ruiyan WANG
1
;
Weixuan DONG
1
;
Xiaoyi DUAN
1
Author Information
- Publication Type:Journal Article
- Keywords: focal prostate cancer; 18F-PSMA-1007; PET/CT; radiomics; differentiation between benign and malignant tumors
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2025;46(2):339-344
- CountryChina
- Language:Chinese
- Abstract: Objective To construct a radiomics model to improve the discriminatory ability of 18 F-PSMA-1007 PET/CT for focal prostate cancer.Methods We retrospectively collected data from 74 patients diagnosed with prostate cancer by biopsy at The First Affiliated Hospital of Xi'an Jiaotong University between July 2020 and April 2024.These patients had focal radionuclide accumulation observed on 18F-PSMA-1007 PET/CT,with the median age of 71 years.Among them,42 patients had a Gleason score＜8 and 32 patients had a Gleason score ≥8.An external validation set was randomly selected based on the timing of examination,while the remaining patients were randomly divided into training and test sets at a 7∶3 ratio.Region of interest(ROI)were semi-automatically drawn on registered images,manually adjusted,and symmetrically shifted to contralateral non-tumor tissue.We made variance and correlation analyses to choose features,and built models with Logistic regression and compared the results with those of visual evaluation.Receiver operating characteristics(ROC)curves were drawn to compare model performance,and subgroup analysis was performed to identify optimal features for distinguishing tumor tissue,based on Gleason score,serum total prostate specific antigen(tPSA)levels,and lesion location.Results A total of eight features were selected.The area under the curve(AUC)for visual evaluation,testing set,and external validation set were 0.858,0.933,and 0.891,respectively.The sensitivity was 0.757,0.800 and 0.917;the specificity was 0.960,0.800 and 0.792,respectively.Subgroup analysis showed that the radiomic features 10percentile and skewness had a high value in tumor differentiation.In tumor tissues,the 10percentile values were higher than in non-tumor tissues across all groups(P-values were 0.012,0.002,＜0.001,＜0.001,＜0.001,and＜0.001).When tPSA≤10 ng/mL and Gleason score ≥8,there was no statistically significant difference in skewness between tumor and non-tumor tissues(P=0.08).When tPSA ≥20 ng/mL,the skewness of non-tumor tissue was slightly higher than that of tumor tissue,but the difference was not statistically significant(P-values were 0.285 and 0.791).When the tumor was located in the posterior part of the prostate(left posterior and right posterior),the skewness was significantly higher in tumor tissue than in non-tumor tissue(P-values＜0.001 for both).Conclusion The radiomics model had better sensitivity and accuracy than visual evaluation in distinguishing focal prostate cancer tumors from non-tumor tissues,but visual evaluation had higher specificity.Skewness and 10percentile had a high value in differential diagnosis.
