Significance of the prostate central gland and total gland volume ratio in the diagnosis of prostate cancer patients in the prostate specific antigen grey zone

Objective To explore the significance of the prostate central gland to total gland volume ratio (PVc/PV) in the diagnosis of prostate cancer (PCa) in patients with prostate specific antigen (PSA) levels in the grey zone (4–10 ng/ml). Methods This retrospective study enrolled patients that had undergone prostate biopsy. The volume of the prostate and the central prostate gland were measured. The differences in PSA, the ratio of free to total PSA (f/tPSA), PSA density (PSAD) and PVc/PV between the PCa and non-PCa groups were compared. Receiver operating characteristic curve analysis for PCa and clinically significant PCa (csPCa) diagnosis were calculated according to PSA (reference), f/tPSA, PSAD and PVc/PV. Results This study enrolled 136 patients. There was no significant difference in PSA and f/tPSA between the PCa and non-PCa groups, while there were significant differences in PSAD and PVc/PV. The area under the curve values of PVc/PV for PCa or csPCa diagnosis were 0.876 and 0.933, respectively; and for PSAD, they were 0.705 and 0.790, respectively. These were significantly different compared with the PSA curve, whereas f/tPSA showed no significant difference from the PSA curve. Conclusion PVc/PV could be a predictor of PCa when PSA is between 4–10 ng/ml.

The clinical guiding value of a radiomics model for androgen deprivation therapy for prostate cancer

Objective Three models were used to evaluate prostate cancer after androgen deprivation therapy (ADT) and to determine the value of detecting residual lesions after treatment. Methods We retrospectively analysed patients with prostate cancer who received ADT from January 2018 to June 2019. Patients were divided into ADT responder and ADT non-responder groups, and clinical risk factors were determined. Regions of interest were manually contoured on each slice on fat-saturated-T2-weighted imaging, and radiomic features were extracted. Uni- and multivariate logistic regression were used to establish radiomics, clinical and combined models. Results There were 23 ADT non-responders and 20 ADT responders. In the clinical model, total prostate-specific antigen concentration and T stage were independent predictors of efficacy (area under the curve (AUC) = 0.774). The characteristics, MinIntensity and Correlation_ angle135_offset4 indicated an effective clinical model (AUC = 0.807). GLCMEntropy_ AllDirection_offset1_SD was the best feature to differentiate residual lesions from the central gland (CG) (Lesion-CG model, AUC = 0.955). Correlation_angle135_offset4, GLCMEntropy_ AllDirection_offset4_SD and GLCMEntropy_AllDirection_offset7_SD differentiated residual lesions from the peripheral zone (PZ) (Lesion-PZ model, AUC = 0.855). The AUC for the combined model was 0.904. Conclusions Our models can guide the clinical treatment of patients with different ADT responses. Furthermore, the radiomics model can detect prostate cancer that is non-responsive to ADT.

Significance of the Prostate Central Gland and Total Gland Volume Ratio in the Diagnosis of Prostate Cancer Patients in the PSA Gray Zone

Objective: To explore the significance of the prostate central gland to total gland volume ratio in the diagnosis of PSA 4-10ng/ml prostate cancer (PCa) patients. Method: A retrospective analysis was performed on patients who had undergone prostate biopsy in our hospital from July 2015 to December 2020.The anteroposterior, transverse and axial diameters of the prostate and the central prostate gland were measured using multiparametric magnetic resonance imaging (mpMRI). The differences in PSA, f/tPSA, PSAD and PVc/PV between the PCa group and the non-PCa group were compared. ROC curves for PCa and clinically significant PCa (csPCa) diagnosis were drawn according to PSA, f/tPSA, PSAD and PVc/PV respectively. Corresponding PSA was used as the reference standard for comparison.Results: There was no statistically significant difference in PSA and f/tPSA between the two groups (P>0.05), while there were statistically significant differences in PSAD and PVc/PV between the two groups (P<0.05). By comparing the AUC values of the ROC curve for any PCa or csPCa, the AUC value of PVc/PV was 0.876 and 0.933, and PSAD was 0.705 and 0.790. This is significantly different from that of the PSA curve (P<0.05), whereas f/tPSA was 0.589 and 0.692 showing no significant difference from the PSA curve (P>0.05).Conclusion: Low volume ratio of central prostate gland PVc/PV has a higher incidence of PCa and csPCa, which can be used as an important reference index for the diagnosis of PCa in PSA 4-10 ng/ml patients.

Diffusion Is Directional: Innovative Diffusion Tensor Imaging to Improve Prostate Cancer Detection

In the prostate, water diffusion is faster when moving parallel to duct and gland walls than when moving perpendicular to them, but these data are not currently utilized in multiparametric magnetic resonance imaging (mpMRI) for prostate cancer (PCa) detection. Diffusion tensor imaging (DTI) can quantify the directional diffusion of water in tissue and is applied in brain and breast imaging. Our aim was to determine whether DTI may improve PCa detection. We scanned patients undergoing mpMRI for suspected PCa with a DTI sequence. We calculated diffusion metrics from DTI and diffusion weighted imaging (DWI) for suspected lesions and normal-appearing prostate tissue, using specialized software for DTI analysis, and compared predictive values for PCa in targeted biopsies, performed when clinically indicated. DTI scans were performed on 78 patients, 42 underwent biopsy and 16 were diagnosed with PCa. The median age was 62 (IQR 54.4–68.4), and PSA 4.8 (IQR 1.3–10.7) ng/mL. DTI metrics distinguished PCa lesions from normal tissue. The prime diffusion coefficient (λ1) was lower in both peripheral-zone (p < 0.0001) and central-gland (p < 0.0001) cancers, compared to normal tissue. DTI had higher negative and positive predictive values than mpMRI to predict PCa (positive predictive value (PPV) 77.8% (58.6–97.0%), negative predictive value (NPV) 91.7% (80.6–100%) vs. PPV 46.7% (28.8–64.5%), NPV 83.3% (62.3–100%)). We conclude from this pilot study that DTI combined with T2-weighted imaging may have the potential to improve PCa detection without requiring contrast injection.

Evaluation of Multimodal Algorithms for the Segmentation of Multiparametric MRI Prostate Images

Prostate segmentation in multiparametric magnetic resonance imaging (mpMRI) can help to support prostate cancer diagnosis and therapy treatment. However, manual segmentation of the prostate is subjective and time-consuming. Many deep learning monomodal networks have been developed for automatic whole prostate segmentation from T2-weighted MR images. We aimed to investigate the added value of multimodal networks in segmenting the prostate into the peripheral zone (PZ) and central gland (CG). We optimized and evaluated monomodal DenseVNet, multimodal ScaleNet, and monomodal and multimodal HighRes3DNet, which yielded dice score coefficients (DSC) of 0.875, 0.848, 0.858, and 0.890 in WG, respectively. Multimodal HighRes3DNet and ScaleNet yielded higher DSC with statistical differences in PZ and CG only compared to monomodal DenseVNet, indicating that multimodal networks added value by generating better segmentation between PZ and CG regions but did not improve the WG segmentation. No significant difference was observed in the apex and base of WG segmentation between monomodal and multimodal networks, indicating that the segmentations at the apex and base were more affected by the general network architecture. The number of training data was also varied for DenseVNet and HighRes3DNet, from 20 to 120 in steps of 20. DenseVNet was able to yield DSC of higher than 0.65 even for special cases, such as TURP or abnormal prostate, whereas HighRes3DNet’s performance fluctuated with no trend despite being the best network overall. Multimodal networks did not add value in segmenting special cases but generally reduced variations in segmentation compared to the same matched monomodal network.

The value of Mr DWI and MRS imaging in the diagnosis of prostate cancer

objective: to investigate the diagnostic value of combined diffusion-weighted magnetic resonance imaging (DWI) and magnetic resonance spectroscopy (MRS) in prostate cancer (PCa).Materials and methods: A total of 25 patients in group A, ranging in age from 67 to 85 years, had diffuse lesions in 3 of them and bone metastases (ilium, pubis, etc.) in 5 of them were confirmed by final examination. All the patients in group A had higher TPSA levels than the reference standard of 4ng/ml within 7 days before mri examination, and the lowest concentration in one patient was 5.02ng/ml. Results greater than 100ng/ml were measured in 5 patients. The sensitivity, specificity and accuracy of DWI, MRS and DWI combined with MRS for PCa diagnosis were analyzed.Results: the mean ADC values of PCa area, peripheral band and central gland in patients with BPH were (0.83±0.12)× 10-3mm /s, (1.82±0.26)× 10-3mm /s and (1.46±0.16)× 10-3mm /s(F=31.1, P < 0.05), respectively.222The mean (Cho+Cr)/Cit values in PCa region, peripheral zone and central gland of BPH patients were 1.55±0.11, 0.53±0.16 and 0.64±0.13, respectively (F=18.2, P < 0.05).There was a statistically significant difference between PCa and BPH patients' peripheral zone and central gland (Cho+Cr)/Cit (P < 0.05), while there was no statistically significant difference between BPH patients' peripheral zone and central gland (Cho+Cr)/Cit (P >, 0.05).The sensitivity, specificity and accuracy of PCa diagnosed by DWI were 79.17%, 80% and 79.63% respectively.The sensitivity, specificity and accuracy of PCa were 87.5%, 86.67% and 87.03% respectively.The sensitivity, specificity and accuracy of DWI combined with MRS in diagnosing PCa were 91.67%, 93.33% and 92.59%, respectively.Conclusion: DWI combined with MRS is better than DWI and MRS alone in the diagnosis of PCa.

Signal Intensity of High B-value Diffusion-weighted Imaging for the Detection of Prostate Cancer

Background: Diffusion-weighted imaging (DWI) is a main component of multiparametric MRI for prostate cancer detection. Recently, high b value DWI has gained more attention because of its capability for tumor characterization.Objectives: To assess based on histopathological findings of transrectal ultrasound (TRUS)-guided prostate biopsy as a reference, an increase in signal intensity of prostatic lesions in comparison with normal background tissue on high b-value diffusion-weighted images could be a sign of malignancy. Material and Methods: Fifty-three consecutive patients retrospectively included in the study. All patients underwent routine TRUS-guided prostate biopsies involving 12 cores after the magnetic resonance imaging (MRI) examinations. In seventeen patients (n =35 lesions), the prostate cancer was histologically confirmed by TRUS-guided prostate biopsy. The biopsy results of other patients were negative. Signal intensities on the high b-value (1600 s/mm2) images of the peripheral zone, the central gland, and the defined lesions were evaluated using region of interest-based measurements. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for prostate cancer detection using signal intensity of high b value diffusion-weighted images were calculated.Results: In the patients with confirmed prostate cancer, fourteen had visually increased SI on the high b-value images. The SI of lesions for these patients was higher than the SI of peripheral zone (22±18%) or central gland (31±20%). In patients with a negative biopsy, eight had visually increased SI on the high b-value images. The SI of lesions for these patients was 23±21% and 35±18% higher than the SI in the peripheral zone and the central gland, respectively. The sensitivity, specificity, PPV, and NPV for prostate cancer using SI of high b value DWI were 71, 87, 62, and 87 %, respectively.Conclusions: Visually increased SI on the high b-value images can be an indication of malignancy, although some benign lesions also show this increase in signal intensity.