Ultrasound elastography, as a new imaging technique to obtain information about tissue elasticity, can directly or indirectly reflect the differences of the inner elastic modulus and other mechanical properties in the tissue, and thus clearly display and position pathological changes and identify lesions. With its rapid development and wide application to clinical practice, ultrasound elastography has become a hot research topic. However, reports are rarely seen at home and abroad about the application of ultrasound elastography in the diagnosis of prostate cancer. This paper introduces the principles and recent development of ultrasound elastography, its application in the diagnosis of prostate cancer, and the trend of research on its diagnostic value.
Elasticity Imaging Techniques ; Humans ; Male ; Prostatic Neoplasms ; diagnostic imaging

OBJECTIVESTo evaluate the clinical significance of PSA and ECT bone scans in the diagnosis of bone metastasis in prostate cancer patients.

METHODSSixty-seven cases of prostate cancer were reviewed, bone metastasis (BM) occurred in 44 cases, and 23 cases without BM (NBM). The relation between PSA, ECT and bone metastasis was analyzed.

RESULTSThe sensitivity of BM with bone scan of ECT was 91.67%. Single local density of radionuclide with bone scan was found in 6 cases, only 2 cases have BM. The value of PSA between BM and Non-BM group had significant difference (87.28 micrograms/L vs 25.37 micrograms/L, P < 0.01). PSA and the degree of bone metastasis was positively correlated. PSA < 10 micrograms/L, the morbidity of BM was 0; PSA 10-20 micrograms/L, 7.69%; PSA 20-60 micrograms/L, 53.33%; PSA 60-100 micrograms/L, 91.67%; and PSA > 100 micrograms/L, 100%.

CONCLUSIONSECT is a high sensitive method in diagnosis of bone metastasis of prostate cancer, but it is not specific in patients with single focus of BM. As for those patients of prostate cancer without any treatment, while PSA < 10 micrograms/L, the morbidity of BM is rare; while PSA > 100 micrograms/L, BM is in high suspect.

Bone Neoplasms ; diagnostic imaging ; secondary ; Humans ; Male ; Prostate-Specific Antigen ; blood ; Prostatic Neoplasms ; diagnosis ; diagnostic imaging ; Tomography, Emission-Computed

Objective: To investigate the risk factors for clinically significant PCa diagnosed by transrectal ultrasound-guided systematic prostate biopsy in patients with MRI-negative and PSA-abnormal findings. METHODS: From January 2014 to December 2017, 335 male patients with MRI-negative (PI-RADS 2.0 score ≤ 2) and PSA-abnormal (4－30 ng/ml ) findings underwent systematic prostate biopsy guided by transrectal ultrasound under local anesthesia in our department. We collected and analyzed the demographic data, clinical symptoms, complications, past history and PSA density (PSAD) of the patients. RESULTS: Clinically significant PCa was diagnosed in 21 (6.3%) of the 335 patients. Multivariate logistic regression analysis showed that the independent risk factors were higher age (AUC: 0.704, P < 0.01) and PSAD (AUC: 0.743, P < 0.01). The cutoff values of age and PSAD were 71 years and 0.18 ng/ml/ml, respectively. CONCLUSIONS Higher age and PSAD are risk factors for clinically significant PCa. Prostate biopsy, even repeated or saturated puncture, is recommended for those aged >71 years old or with PSAD >0.18 ng/ml/ml so as to avoid missed diagnosis and unnecessary invasive biopsy as well. /.
Aged ; Humans ; Magnetic Resonance Imaging ; Male ; Prostate-Specific Antigen ; Prostatic Neoplasms/diagnostic imaging* ; Risk Factors

Magnetic resonance imaging (MRI) is a very important imaging method for diagnosis and treatment of prostate cancer (PCa) in clinical practice. As functional MRI is growing and maturing, its quantitative parameters are expected to enhance the clinical value of MRI furtherly. Intravoxel incoherent motion diffusion imaging, diffusion tensor imaging, and diffusion kurtosis imaging, which were derived from diffusion weighted imaging, have provided richer and more accurate parameters. The newly-developed magnetic resonance elastography can complement the mechanical characteristics of PCa.
Diffusion Magnetic Resonance Imaging ; Diffusion Tensor Imaging ; Humans ; Magnetic Resonance Imaging ; Male ; Motion ; Prostatic Neoplasms/diagnostic imaging*

OBJECTIVETo report our experience of ultrasound guided transperineal 6-core prostate biopsy (UG6CPB) in the diagnosis of prostate cancer (PCa).

METHODSIn a prospective study, we performed UG6CPB in 104 suspected PCa patients with tPSA more than 4 microg/L and analysed the positive rate and complications of the diagnostic approach.

RESULTSPCa was detected in 24 of the 104 patients (23%), with low grade Gleason 2 to 4 in 3 cases (12.5%), intermediate grade Gleason 5 to 7 in 15 (62.5%) and high grade Gleason 8 to 10 in the remaining 6 (25%). Complications included temporary hematuria in 5 patients (4.8%), mild postbiopsy perineal discomfort in 5 (4.8%) and fever in 4 (3.8%). TPSA > or =10 microg/L, fPSA > or = 2 microg/L, fPSA/tPSA < 0.16, PSAD > or = 0.2 and prostate volume < 40 ml were the significant influencing factors of biopsy positive rate (P < 0.05).

CONCLUSIONUG6CPB is an exact and a safe way of detecting PCa.

Biopsy, Needle ; methods ; Humans ; Male ; Perineum ; Prospective Studies ; Prostate-Specific Antigen ; blood ; Prostatic Hyperplasia ; diagnostic imaging ; pathology ; Prostatic Neoplasms ; diagnostic imaging ; pathology ; Ultrasonography

To explore the value of prostate imaging reporting and data system version 2 (PI-RADS V2) combined with quantitative parameters derived from apparent diffusion coefficient (ADC) map in the diagnosis of peripheral zone prostate cancer.
 Methods: A total of 50 patients who underwent prostate multiparametric MRI (mpMRI) with suspicious peripheral nodules were retrospectively enrolled, and all patients were biopsy-proven histologically. Two radiologists analyzed the position and category of peripheral zone lesions based on PI-RADS V2. Then 12 ADC quantitative parameters were calculated regarding each lesion on the ADC map by post-processing software. The lesions were divided into malignant group and benign group according to histopathological findings. The ADC quantitative parameters between groups were compared, and stepwise logistic regression analysis was used to build a discriminative model. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were performed to evaluate the diagnostic power and clinical benefit.
 Results: Twenty-eight peripheral zone prostate malignant lesions and 25 benign lesions were obtained finally. The area under the ROC curve, sensitivity and specificity to differentiate peripheral zone prostate malignant from benign lesions were as follows: 0.803, 60.71%, 92.00% (PI-RADS V2 score), 0.857, 89.29%, 76.00% (ADC model), and 0.891, 71.43%, 92.00% (combined model), respectively. The discriminative power of the combined model was significantly improved compared with PI-RADS V2 score (P=0.012). The combined model had relatively optimal overall net benefit, which outperformed the PI-RADS V2 score when threshold probability varied in the range of 0.05-0.27 and 0.46-0.81.
 Conclusion: PI-RADS V2 combined with quantitative analysis of ADC map improve the power in discriminating peripheral zone prostate cancer from benign lesions, and the clinical benefit as well.
Data Systems ; Diffusion Magnetic Resonance Imaging ; Humans ; Magnetic Resonance Imaging ; Male ; Prostatic Neoplasms ; diagnostic imaging ; Retrospective Studies

Objective To investigate the feasibility of using low-dose prostate CT perfusion (pCTP)on a third-generation dual-source CT. Methods Nine patients with elevated prostate-specific antigen underwent pCTP before having prostate biopsy. We measured the blood flow (BF),blood volume (BV),mean transit time (MTT),permeability surface (PS),and time to peak(TTP)of both lesions and normal prostate tissue. The effective dose (ED)was calculated. Results Of the 9 cases,6 were prostate cancers and 3 were prostate hyperplasia with chronic inflammation. The average ED of the 9 pCTPs was (3.5±0.3)mSv. The BF (t=4.64,P<0.001),BV (t=3.27,P<0.001),and PS (t=3.58,P=0.004)of prostate cancer were significantly higher than those of normal prostate tissue and TTP (t=-1.26,P<0.001)of prostate cancer was significantly lower than that of normal prostate tissue. BF (t=3.96,P=0.001)and PS (t=2.91,P=0.021)of prostate hyperplasia with chronic inflammation were also significantly higher and TTP (t=-1.19,P<0.001)was significantly lower than those of normal prostate tissue. TTP of prostate cancer was significantly lower than that of prostate hyperplasia with chronic inflammation (t=-2.56,P=0.049). Conclusion sLow-dose pCTP is feasible on third-generation dual-source CT. The BF,PS,and TTP differ among prostate cancer,prostate hyperplasia with chronic inflammation,and normal prostate tissue.
Blood Volume ; Feasibility Studies ; Humans ; Male ; Prostatic Neoplasms ; diagnostic imaging ; Tomography, X-Ray Computed ; methods

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.
Male ; Humans ; Prostate/pathology* ; Prostate-Specific Antigen/analysis* ; Prostatic Neoplasms/diagnostic imaging* ; Biopsy ; Nomograms ; Retrospective Studies

OBJECTIVE: To establish a Parotid Imaging Reporting and Data System (PI-RADS) for CT diagnosis of the parotid gland neoplasms and to investigate the clinical applicable value and feasibility of PI-RADS. METHODS: Patients who had been diagnosed with primary parotid gland neoplasms and had received surgical treatments in Peking University School and Hospital of Stomatology during the period of January 2013 to December 2016 were included in this study. The diagnoses were confirmed by the postoperative pathological examinations in all the patients. The CT imaging data of all patients were retrospectively reviewed and analyzed by two readers in consensus. Imaging characteristics related to the parotid neoplasms were extracted and quantified. Based on comprehensive analysis of the imaging characteristics, the probabilities of the benign and malignant neoplasms were evaluated and classified into six grades, PI-RADS 1-6 (PI-RADS 1: normal parotid gland; PI-RADS 2: confidently benign lesions; PI-RADS 3: probably benign lesions without confirmed evidence of malignancy; PI-RADS 4: suspected malignancy without sufficient evidence of malignancy; PI-RADS 5: confidently malignant lesions; PI-RADS 6: lesions with confirmed pathological evidence of malignancy). RESULTS: A total of 897 patients with 1 003 parotid lesions were included. The lesions included 905 benign and 98 malignant lesions. The proportions of the malignancies in PI-RADS 2, PI-RADS 3, PI-RADS 4 and PI-RADS 5 according to the two readers in consensus were 0.4%, 5.7%, 35.5% and 96.7% respectively. The overall Cohen's Kappa test showed medium consistency between the two independent researchers (κ=0.614, P<0.001, 95%CI: 0.569-0.695). Pearson Chi-square test showed that the proportions of malignancies increased with the diagnostic PI-RADS grades (Cochran-Armitage trend test, Z=-15.579, P<0.001). The results of Pearson Chi-square tests showed significant differences between the grades [PI-RADS 2 and 3 (χ²=12.048, P=0.001); PI-RADS 3 and 4 (χ²=75.231, P<0.001); PI-RADS 4 and 5 (χ²=32.266, P<0.001)]. CONCLUSION PI-RADS can be used to evaluate the risk of malignancy and will be helpful to improve the imaging diagnosis and clinical treatment of parotid gland neoplasms.
Humans ; Magnetic Resonance Imaging ; Male ; Parotid Gland/diagnostic imaging* ; Parotid Neoplasms ; Prostatic Neoplasms ; Retrospective Studies ; Tomography, X-Ray Computed

Magnetic resonance (MR) imaging is an important tool for prostate cancer diagnosis, and accurate segmentation of MR prostate regions by computer-aided diagnostic techniques is important for the diagnosis of prostate cancer. In this paper, we propose an improved end-to-end three-dimensional image segmentation network using a deep learning approach to the traditional V-Net network (V-Net) network in order to provide more accurate image segmentation results. Firstly, we fused the soft attention mechanism into the traditional V-Net's jump connection, and combined short jump connection and small convolutional kernel to further improve the network segmentation accuracy. Then the prostate region was segmented using the Prostate MR Image Segmentation 2012 (PROMISE 12) challenge dataset, and the model was evaluated using the dice similarity coefficient (DSC) and Hausdorff distance (HD). The DSC and HD values of the segmented model could reach 0.903 and 3.912 mm, respectively. The experimental results show that the algorithm in this paper can provide more accurate three-dimensional segmentation results, which can accurately and efficiently segment prostate MR images and provide a reliable basis for clinical diagnosis and treatment.
Male ; Humans ; Prostate/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Magnetic Resonance Imaging/methods* ; Imaging, Three-Dimensional/methods* ; Prostatic Neoplasms/diagnostic imaging*