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Xu L, Peng Q, Zhang G, Zhang D, Zhang J, Zhang X, Bai X, Chen L, Guo E, Xiao Y, Jin Z, Sun H. Development of preoperative nomograms to predict the risk of overall and multifocal positive surgical margin after radical prostatectomy. Cancer Imaging 2024; 24:104. [PMID: 39118144 PMCID: PMC11312749 DOI: 10.1186/s40644-024-00749-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 07/24/2024] [Indexed: 08/10/2024] Open
Abstract
OBJECTIVE To develop preoperative nomograms using risk factors based on clinicopathological and MRI for predicting the risk of positive surgical margin (PSM) after radical prostatectomy (RP). PATIENTS AND METHODS This study retrospectively enrolled patients who underwent prostate MRI before RP at our center between January 2015 and November 2022. Preoperative clinicopathological factors and MRI-based features were recorded for analysis. The presence of PSM (overall PSM [oPSM]) at pathology and the multifocality of PSM (mPSM) were evaluated. LASSO regression was employed for variable selection. For the final model construction, logistic regression was applied combined with the bootstrap method for internal verification. The risk probability of individual patients was visualized using a nomogram. RESULTS In all, 259 patients were included in this study, and 76 (29.3%) patients had PSM, including 40 patients with mPSM. Final multivariate logistic regression revealed that the independent risk factors for oPSM were tumor diameter, frank extraprostatic extension, and annual surgery volume (all p < 0.05), and the nomogram for oPSM reached an area under the curve (AUC) of 0.717 in development and 0.716 in internal verification. The independent risk factors for mPSM included the percentage of positive cores, tumor diameter, apex depth, and annual surgery volume (all p < 0.05), and the AUC of the nomogram for mPSM was 0.790 in both development and internal verification. The calibration curve analysis showed that these nomograms were well-calibrated for both oPSM and mPSM. CONCLUSIONS The proposed nomograms showed good performance and were feasible in predicting oPSM and mPSM, which might facilitate more individualized management of prostate cancer patients who are candidates for surgery.
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Affiliation(s)
- Lili Xu
- Department of Radiology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, No. 1 East Banshan Road, Gongshu District, Hangzhou, 310022, China
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Qianyu Peng
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Gumuyang Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Daming Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Jiahui Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Xiaoxiao Zhang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Xin Bai
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Li Chen
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Erjia Guo
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Yu Xiao
- Department of Pathology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
- National Center for Quality Control of Radiology, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
| | - Hao Sun
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
- National Center for Quality Control of Radiology, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
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Meng S, Gan W, Chen L, Wang N, Liu A. Intravoxel incoherent motion predicts positive surgical margins and Gleason score upgrading after radical prostatectomy for prostate cancer. LA RADIOLOGIA MEDICA 2023:10.1007/s11547-023-01645-2. [PMID: 37277573 DOI: 10.1007/s11547-023-01645-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 05/02/2023] [Indexed: 06/07/2023]
Abstract
BACKGROUND Whether Intravoxel incoherent motion (IVIM) can be used as a predictive tool of positive surgical margins (PSMs) and Gleason score (GS) upgrading in prostate cancer (PCa) patients after radical prostatectomy (RP) still remains unclear. The aim of this study is to explore the ability of IVIM and clinical characteristics to predict PSMs and GS upgrading. METHODS A total of 106 PCa patients after RP who underwent pelvic mpMRI (multiparametric Magnetic Resonance Imaging) between January 2016 and December 2021 and met the requirements were retrospectively included in our study. IVIM parameters were obtained using GE Functool post-processing software. Logistic regression models were fitted to confirm the predictive risk factor of PSMs and GS upgrading. The area under the curve and fourfold contingency table were used to evaluate the diagnostic efficacy of IVIM and clinical parameters. RESULTS Multivariate logistic regression analyses revealed that percent of positive cores, apparent diffusion coefficient and molecular diffusion coefficient (D) were independent predictors of PSMs (Odds Ratio (OR) were 6.07, 3.62 and 3.16, respectively), Biopsy GS and pseudodiffusion coefficient (D*) were independent predictors of GS upgrading (OR were 0.563 and 7.15, respectively). The fourfold contingency table suggested that combined diagnosis increased the ability of predicting PSMs but had no advantage in predicting GS upgrading except the sensitivity from 57.14 to 91.43%. CONCLUSIONS IVIM showed good performance in predicting PSMs and GS upgrading. Combining IVIM and clinical factors enhanced the performance of predicting PSMs, which may contribute to clinical diagnosis and treatment.
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Affiliation(s)
- Shuang Meng
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Wanting Gan
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Lihua Chen
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Nan Wang
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China
| | - Ailian Liu
- Department of Radiological, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Dalian, 116011, China.
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Meng S, Chen L, Zhang Q, Wang N, Liu A. Multiparametric MRI-based nomograms in predicting positive surgical margins of prostate cancer after laparoscopic radical prostatectomy. Front Oncol 2022; 12:973285. [PMID: 36172161 PMCID: PMC9510973 DOI: 10.3389/fonc.2022.973285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 08/11/2022] [Indexed: 11/26/2022] Open
Abstract
Background Positive surgical margins (PSMs) are an independent risk factor of biochemical recurrence in patients with prostate cancer (PCa) after laparoscopic radical prostatectomy; however, limited MRI-based predictive tools are available. This study aimed to develop a novel nomogram combining clinical and multiparametric MRI (mpMRI) parameters to reduce PSMs by improving surgical planning. Methods One hundred and three patients with PCa (55 patients with negative surgical margins [NSMs] and 48 patients with PSMs) were included in this retrospective study. The following parameters were obtained using GE Functool post-processing software: diffusion-weighted imaging (DWI); intravoxel incoherent motion model (IVIM); and diffusion kurtosis imaging (DKI). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to analyze the data set to select the optimal MRI predictors. Preoperatively clinical parameters used to build a clinical nomogram (C-nomogram). Multivariable logistic regression analysis was used to build an MRI nomogram (M-nomogram) by introducing the MRI parameters. Based on the MRI and clinical parameters, build an MRI combined with clinical parameters nomogram (MC-nomogram). Comparisons with the M-nomogram and MC-nomogram were based on discrimination, calibration, and decision curve analysis (DCA). A 3-fold cross-validation method was used to assess the stability of the nomogram. Results There was no statistical difference in AUC between the C-nomogram (sensitivity=64%, specificity=65% and AUC=0.683), the M-nomogram (sensitivity=57%, specificity=88% and AUC=0.735) and the MC-nomogram (sensitivity= 64%, specificity=82% and AUC=0.756). The calibration curves of the three nomograms used to predict the risk of PSMs in patients with PCa showed good agreement. The net benefit of the MC-nomogram was higher than the others (range, 0.2-0.7). Conclusions The mpMRI-based nomogram can predict PSMs in PCa patients. Although its AUC (0.735) is not statistically different from that of the clinical-based nomogram AUC (0.683). However, mpMRI-based nomogram has higher specificity (88% VS. 63%), model stability, and clinical benefit than clinical-based nomogram. And the predictive ability of mpMRI plus clinical parameters for PSMs is further improved.
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