Assessment Of Prostate Cancer Aggressiveness Research Articles

The value of synthetic magnetic resonance imaging in the diagnosis and assessment of prostate cancer aggressiveness.

Synthetic magnetic resonance imaging (SyMRI) is a fast, standardized, and robust novel quantitative technique that has the potential to circumvent the subjectivity of interpretation in prostate multiparametric magnetic resonance imaging (mpMRI) and the limitations of existing MRI quantification techniques. Our study aimed to evaluate the potential utility of SyMRI in the diagnosis and aggressiveness assessment of prostate cancer (PCA). We retrospectively analyzed 309 patients with suspected PCA who had undergone mpMRI and SyMRI, and pathologic results were obtained by biopsy or PCA radical prostatectomy (RP). Pathological types were classified as PCA, benign prostatic hyperplasia (BPH), or peripheral zone (PZ) inflammation. According to the Gleason Score (GS), PCA was divided into groups of intermediate-to-high risk (GS ≥4+3) and low-risk (GS ≤3+4). Patients with biopsy-confirmed low-risk PCA were further divided into upgraded and nonupgraded groups based on the GS changes of the RP results. The values of the apparent diffusion coefficient (ADC), T1, T2 and proton density (PD) of these lesions were measured on ADC and SyMRI parameter maps by two physicians; these values were compared between PCA and BPH or inflammation, between the intermediate-to-high-risk and low-risk PCA groups, and between the upgraded and nonupgraded PCA groups. The risk factors affecting GS grades were identified via univariate analysis. The effects of confounding factors were excluded through multivariate logistic regression analysis, and independent predictive factors were calculated. Subsequently, the ADC+Sy(T2+PD) combined models for predicting PCA risk grade or GS upgrade were constructed through data processing analysis. The diagnostic performance of each parameter and the ADC+Sy(T2+PD) model was analyzed. The calibration curve was calculated by the bootstrapping internal validation method (200 bootstrap resamples). The T1, T2, and PD values of PCA were significantly lower than those of BPH or inflammation (P≤0.001) in both the PZ or transitional zone. Among the 178 patients with PCA, intermediate-to-high-risk PCA group had significantly higher T1, T2, and PD values but lower ADC values compared with the low-risk group (P<0.05), and the diagnostic efficacy of each single parameter was similar (P>0.05). The ADC+Sy(T2+PD) model showed the best performance, with an area under the curve (AUC) 0.110 [AUC =0.818; 95% confidence interval (CI): 0.754-0.872] higher than that of ADC alone (AUC =0.708; 95% CI: 0.635-0.774) (P=0.003). Among the 68 patients initially classified as PCA in the low-risk group by biopsy, PCA in the postoperative upgraded GS group had significantly higher T1, T2, and PD values but lower ADC values than did those in the nonupgraded group (P<0.01). In addition, the ADC+Sy(T2+PD) model better predicted the upgrade of GS, with a significant increase in AUC of 0.204 (AUC =0.947; 95% CI: 0.864-0.987) compared with ADC alone (AUC =0.743; 95% CI: 0.622-0.841) (P<0.001). Quantitative parameters (T1, T2, and PD) derived from SyMRI can help differentiate PCA from non-PCA. Combining SyMRI parameters with ADC significantly improved the ability to differentiate between intermediate-to-high risk PCA from low-risk PCA and could predict the upgrade of low-risk PCA as confirmed by biopsy.

Role of DWI/ADC in the Assessment of Prostate Cancer Aggressiveness and Its Correlation to Gleason Score

Background Cancer prostate represents a major health problem. it is one of the most common solid malignancies among male population. Prostate cancer (PCa) is considered one of the most common cancers among male population. Its incidence increases with age, ranging from 34% in the fifth decade, to 70% over the 80 years. Aim of the Work The objective of the study is to correlate and compare the DWI and ADC values of prostate cancer with the histopathological grading via Gleason score. Patients and Methods During a period of 6 months duration thirty patients were enrolled in the study. All patients with elevated PSA values greater than 4 ng/ml underwent sextant TRUS guided biopsies. MRI examination was done either prior to the TRUS biopsy or at least 3 weeks after the TRUS biopsy. Results In our study, we found that the ADC values correlated significantly with Gleason score of prostate cancer based on TRUS biopsy with significant p value &amp;lt; 0.001 and were significantly predictive of high-grade prostate cancer. This outcome agrees with recent reports that found an inverse correlation between ADC and Gleason score. They confrmed the correlation between ADC derived DWI and tumor alteration. ADC analysis seems to show a high capability in defining the tumor aggressiveness, as in monitoring radiation therapy effect or surgical recurrence. Conclusion ADC values showed a negative correlation with GS. This study suggests that ADC values may allow the noninvasive assessment of biological aggressiveness of prostate cancer, which may contribute in targeting biopsy to MRI-positive foci using a fusion of MRI and transrectal ultrasound. Incorporating the GS on targeted biopsy with the ADC value will further improve the detection of highgrade cancer foci also plays a role in planning initial treatment strategies.

Assessing the microarchitecture and microenvironment of cancer in vivo by photoacoustic imaging techniques

Majority of current studies on photoacoustic (PA) imaging are focused on the total signal magnitudes as the reflection of the macroscopic optical absorption by specific chemical contents at single or multiple optical wavelengths. Our recent research has demonstrated that the frequency domain power distribution of radio-frequency PA signals contains the microscopic information of the optically absorbing materials in biological samples. In this research, I will present our recent development of quantitative PA methods for in vivo evaluation of histological microarchitectures of biological tissues as well as potential clinical applications of these methods such as the assessment of prostate cancer aggressiveness. In addition, powered by our recently developed polyacrylamide hydrogel nanoparticles containing a variety of functional contrast agents, multi-wavelength PA imaging plus spectral unmixing technique can enable quantitative mapping of the chemical and metabolic properties in cancer microenvironments, such as tissue oxygenation, pH level, and ion concentrations. Imaging of these chemical makeups of an entire tumor in vivo, non-invasively, with high sensitivity and high spatial resolution can shed new light to the understanding of cancer onset, progress, and responses to therapies.

Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI.

Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiveness. We optimized several ML/DL frameworks on T2w, ADC and T2w+ADC data, using a patient-based nested validation scheme. The dataset was composed of 112 patients (132 peripheral lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥ 3) acquired following both PI-RADS 2.0 and 2.1 guidelines. Firstly, ML/DL frameworks trained and validated on PI-RADS 2.0 data were tested on both PI-RADS 2.0 and 2.1 data. Then, we trained, validated and tested ML/DL frameworks on a multi PI-RADS dataset. We reported the performances in terms of Area Under the Receiver Operating curve (AUROC), specificity and sensitivity. The ML/DL frameworks trained on T2w data achieved the overall best performance. Notably, ML and DL frameworks trained and validated on PI-RADS 2.0 data obtained median AUROC values equal to 0.750 and 0.875, respectively, on unseen PI-RADS 2.0 test set. Similarly, ML/DL frameworks trained and validated on multi PI-RADS T2w data showed median AUROC values equal to 0.795 and 0.750, respectively, on unseen multi PI-RADS test set. Conversely, all the ML/DL frameworks trained and validated on PI-RADS 2.0 data, achieved AUROC values no better than the chance level when tested on PI-RADS 2.1 data. Both ML/DL techniques applied on mpMRI seem to be a valid aid in predicting PCa aggressiveness. In particular, ML/DL frameworks fed with T2w images data (objective, fast and non-invasive) show good performances and might support decision-making in patient diagnostic and therapeutic management, reducing intra- and inter-reader variability.

The Assessment of Prostate Cancer Aggressiveness Using a Combination of Quantitative Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

ObjectiveTo explore the value of combining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters with apparent diffusion coefficient (ADC) values in the diagnosis of prostate cancer.MethodsThe clinical data of 146 patients with prostate lesions, including 87 patients with prostate cancer (PCa) and 59 with benign prostatic hyperplasia (BPH), were collected. After DCE-MRI and diffusion-weighted imaging (DWI) prostate scans, the magnitude of the DCE-MRI transfer constant (Ktrans), rate constant (kep), the volume of the extravascular extracellular space (ve), and the ADC between the groups were compared, and the correlations between the DCE-MRI parameters and Gleason scores were analyzed. The diagnostic efficacy of these quantitative parameters was assessed by the area under the receiver operating characteristic (ROC) curve.ResultsThe DCE-MRI parameters Ktrans and kep were significantly greater in the PCa group than in the BPH group (p < 0.05). The ROC curve showed the area under the Ktrans, kep, and ADC curves to be 0.665, 0.658, and 0.782, respectively. When all three quantitative indicators were combined, the area under the ROC curve was 0.904, with sensitivity and specificity rates of 83.6% and 93.7%, respectively. The Gleason scores were positively correlated with the Ktrans, kep, and ve (r = 0.39, 0.572, 0.30, respectively; p < 0.05) and negatively correlated with the ADC (r = –0.525; p < 0.05).ConclusionThe DCE-MRI quantitative parameters Ktrans and kep, as well as the ADC value, provided effective references for the differential diagnosis of PCa and BPH, as well as more precise and reliable quantitative parameters for grading the aggressiveness of PCa.

P46 - Assessment of prostate cancer aggressiveness using metabolomics evaluation of urine by NMR spectroscopy

P46 - Assessment of prostate cancer aggressiveness using metabolomics evaluation of urine by NMR spectroscopy

Biofluid quantification of TWEAK/Fn14 axis in combination with a selected biomarker panel improves assessment of prostate cancer aggressiveness

BackgroundConventional clinical biomarkers cannot accurately differentiate indolent from aggressive prostate cancer (PCa). We investigated the usefulness of a biomarker panel measured exclusively in biofluids for assessment of PCa aggressiveness.MethodsWe collected biofluid samples (plasma/serum/semen/post-prostatic massage urine) from 98 patients that had undergone radical prostatectomy. Clinical biochemistry was performed and several cytokines/chemokines including soluble(s) TWEAK, sFn14, sCD163, sCXCL5 and sCCL7 were quantified by ELISA in selected biofluids. Also, the expression of KLK2, KLK3, Fn14, CD163, CXCR2 and CCR3 was quantified by real-time PCR in semen cell sediment. Univariate, logistic regression, and receiver operating characteristic (ROC) analyses were used to assess the predictive ability of the selected biomarker panel in conjunction with clinical and metabolic variables for the evaluation of PCa aggressiveness.ResultsTotal serum levels of prostate-specific antigen (PSA), semen levels of sTWEAK, fasting glycemia and mRNA levels of Fn14, KLK2, CXCR2 and CCR3 in semen cell sediment constituted a panel of markers that was significantly different between patients with less aggressive tumors [International Society of Urological Pathology (ISUP) grade I and II] and those with more aggressive tumors (ISUP grade III, IV and V). ROC curve analysis showed that this panel could be used to correctly classify tumor aggressiveness in 90.9% of patients. Area under the curve (AUC) analysis revealed that this combination was more accurate [AUC = 0.913 95% confidence interval (CI) 0.782–1] than a classical non-invasive selected clinical panel comprising age, tumor clinical stage (T-classification) and total serum PSA (AUC = 0.721 95% CI 0.613–0.830).ConclusionsTWEAK/Fn14 axis in combination with a selected non-invasive biomarker panel, including conventional clinical biochemistry, can improve the predictive power of serum PSA levels and could be used to classify PCa aggressiveness.

A novel approach for assessment of prostate cancer aggressiveness using survivin-driven tumour-activatable minicircles

Early and accurate detection of cancer is essential to optimising patient outcomes. Of particular importance to prostate cancer is the ability to determine the aggressiveness of a primary tumour, which allows for effective management of patient care. In this work, we propose using gene vectors called tumour-activatable minicircles which deliver an exogenously encoded reporter gene into cancer cells, forcing them to produce a unique and sensitive biomarker. These minicircles express a blood reporter protein called secreted embryonic alkaline phosphatase mediated by the tumour-specific survivin promoter, which exhibits activity graded to prostate cancer aggressiveness. Together, these components underlie a detection system where levels of blood reporter are indicative of not only the presence, but also the metastatic potential of a tumour. Our goal was to assess the ability of tumour-activatable minicircles to detect and characterise primary prostate lesions. Our minicircles produced reporter levels related to survivin expression across a range of prostate cancer cell lines. When survivin-driven minicircles were administered intratumourally into mice, reporter levels in blood samples were significantly higher (p < 0.05) in mice carrying prostate tumours of high versus low-aggressiveness. Continued development of this gene-based system could provide clinicians with a powerful tool to evaluate prostate cancer aggressiveness using a sensitive and affordable blood assay.

Assessment of prostate cancer aggressiveness using apparent diffusion coefficient values: impact of patient race and age.

To assess the impact of patient race and age on the performance of apparent diffusion coefficient (ADC) values for assessment of prostate cancer aggressiveness. 457 prostate cancer patients who underwent 3T phased-array coil prostate MRI including diffusion-weighted imaging (DWI; maximal b-value 1000s/mm2) before prostatectomy were included. Mean ADC of a single dominant lesion was measured in each patient, using histopathologic findings from the prostatectomy specimen as reference. In subsets defined by race and age, ADC values were compared between Gleason score (GS)≤3+4 and GS≥4+3 tumors. 81% of patients were Caucasian, 12% African-American, 7% Asian-American. 13% were <55years, 42% 55-64years, 41% 65-74years, and 4% ≥75years. 63% were GS≤3+4, 37% GS≥4+3. ADC was significantly lower in GS≥4+3 tumors than in GS≤3+4 tumors in the entire cohort, as well as in Caucasian, African-American, and all four age groups (P≤0.015). AUC for differentiation of GS≤3+4 and GS≥4+3 as well as optimal ADC threshold was Caucasian: 0.73/≤848; African-American: 0.76/≤780; Asian-American: 0.66/≤839: <55years, 0.73/≤830; 55-64years, 0.71/≤800; 65-74years, 0.74/≤872; ≥75years, 0.79/≤880. A race-optimized ADC threshold resulted in higher specificity in African-American than Caucasian men (84.9% vs. 67.1%, P=0.045); age-optimized ADC threshold resulted in higher sensitivity in patients aged ≥75years than <55years or 55-64years (100.0% vs. 53.6%-73.3%; P<0.001). Patients' race and age may impact the diagnostic performance and optimal threshold when applying ADC values for evaluation of prostate cancer aggressiveness.

Apparent diffusion coefficient values are superior to transrectal ultrasound-guided prostate biopsy for the assessment of prostate cancer aggressiveness.

Background Few studies have focused on comparing the utility of diffusion-weighted imaging (DWI) and transrectal ultrasound (TRUS)-guided biopsy in predicting prostate cancer aggressiveness. Whether apparent diffusion coefficient (ADC) values can provide more information than TRUS-guided biopsy should be confirmed. Purpose To retrospectively assess the utility of ADC values in predicting prostate cancer aggressiveness, compared to the TRUS-guided prostate biopsy Gleason score (GS). Material and Methods The DW images of 54 patients with biopsy-proven prostate cancer were obtained using 1.5-T magnetic resonance (MR). The mean ADC values of cancerous areas and biopsy GS were correlated with prostatectomy GS and D'Amico clinical risk scores, respectively. Meanwhile, the utility of ADC values in identifying high-grade prostate cancer (with Gleason 4 and/or 5 components in prostatectomy) in patients with a biopsy GS ≤ 3 + 3 = 6 was also evaluated. Results A significant negative correlation was found between mean ADC values of cancerous areas and the prostatectomy GS ( P < 0.001) and D'Amico clinical risk scores ( P < 0.001). No significant correlation was found between biopsy GS and prostatectomy GS ( P = 0.140) and D'Amico clinical risk scores ( P = 0.342). Patients harboring Gleason 4 and/or 5 components in prostatectomy had significantly lower ADC values than those harboring no Gleason 4 and/or 5 components ( P = 0.004). Conclusion The ADC values of cancerous areas in the prostate are a better indicator than the biopsy GS in predicting prostate cancer aggressiveness. Moreover, the use of ADC values can help identify the presence of high-grade tumor in patients with a Gleason score ≤ 3 + 3 = 6 during biopsy.

Assessment of Prostate Cancer Aggressiveness by Use of the Combination of Quantitative DWI and Dynamic Contrast-Enhanced MRI.

The objective of this study was to investigate whether the apparent diffusion coefficient (ADC) value from DWI and the forward volume transfer constant (K(trans)) value from dynamic contrast-enhanced MRI independently predict prostate cancer aggressiveness, and to determine whether the combination of both parameters performs better than either parameter alone in assessing tumor aggressiveness before treatment. This retrospective study included 158 men with histopathologically confirmed prostate cancer who underwent 3-T MRI before undergoing prostatectomy in 2011. Whole-mount step-section pathologic maps identified 195 prostate cancer foci that were 0.5 mL or larger; these foci were then volumetrically assessed to calculate the per-tumor ADC and K(trans) values. Associations between MRI and histopathologic parameters were assessed using Spearman correlation coefficients, univariate and multivariable logistic regression, and AUCs. The median ADC and K(trans) values showed moderate correlation only for tumors for which the Gleason score (GS) was 4 + 4 or higher (ρ = 0.547; p = 0.042). The tumor ADC value was statistically significantly associated with all dichotomized GSs (p < 0.005), including a GS of 3 + 3 versus a GS of 3 + 4 or higher (AUC, 0.693; p = 0.001). The tumor K(trans) value differed statistically significantly only between tumors with a GS of 3 + 3 and those with a primary Gleason grade of 4 (p ≤ 0.015), and it made a statistically significant contribution only in differentiating tumors with a GS of 4 + 3 or higher (AUC, 0.711; p < 0.001) and those with a GS of 4 + 4 or higher (AUC, 0.788; p < 0.001) from lower-grade tumors. Combining ADC and K(trans) values improved diagnostic performance in characterizing tumors with a GS of 4 + 3 or higher and those with a GS of 4 + 4 or higher (AUC, 0.739 and 0.856, respectively; p < 0.01). Although the ADC value helped to differentiate between all GSs, the K(trans) value was only a benefit in characterizing more aggressive tumors. Combining these parameters improves their performance in identifying patients with aggressive tumors who may require radical treatment.

Prostate cancer: the correlation between apparent diffusion coefficient values obtained from high resolution diffusion-weighted imaging and Gleason scores

Objective To compare ADC values obtained from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) techniques of prostate cancer and to investigate the correlation between RS-EPI ADC values and Gleason scores. Methods A retrospective analysis of RS-EPI and SS-EPI DWI were performed in 23 patients with pathologically confirmed prostate cancer. Routine MRI, RS-EPI DWI and SS-EPI DWI were obtained prior to ultrasound guided systemic biopsy in all cases. According to the location of lesion from biopsy report, a ROI was drawn on ADC map obtained from RS-EPI DWI and SS-EPI DWI, respectively, at cancerous foci with low T2WI and high DWI signal intensity. Foci were classified into well differentiated group (Gleason score≤6) and poorly and moderately differentiated group (Gleason score≥7). ADC values between RS-EPI and SS-EPI were compared by using t test. The relationship between ADC values and Gleason scores was assessed using Spearman test. The sensitivity and specificity of RS-EPI ADC value for differential diagnosis of two groups and the best cutoff were evaluated from ROC. Results Twenty nine well differentiated foci and 126 poorly and moderately differentiated foci were identified. The mean RS-EPI ADC value and the mean SS-EPI ADC value of well differentiated group and poorly and moderately differentiated group were (1.136 ± 0.136) × 10-3mm2/s, (1.125±0.198)×10-3mm2/s; (0.891±0.161)×10-3mm2/s, (0.875 ±0.184)×10-3mm2/s, respectively. Neither well differentiated group nor poorly and moderately differentiated group had a significant difference between the mean ADC value of two techniques (t values were 0.359 and 1.727, P values were 0.722 and 0.087, respectively). Either mean RS-EPI ADC value or mean SS-EPI ADC value between two groups had a significant difference (t values were 7.572 and 6.499, P<0.01, respectively). There was an inverse relationship between ADC values obtained from RS-EPI and SS-EPI and Gleason scores (r values were -0.638 and -0.565, P<0.01, respectively). When the cutoff value was 1.041×10-3mm2/s, the sensitivity and specificity of RS-EPI ADC value to differentiate two groups were 85.7% (108/126), 86.2% (25/29), respectively, and the area under ROC curve was 0.882. Conclusions There were no significant difference between ADC values obtained from RS-EPI and SS-EPI. ADC values of both techniques had positive correlation with Gleason scores. RS-EPI ADC values may have potential to allow noninvasive assessment of prostate cancer aggressiveness, which could help in the stratification of patients for appropriate therapy. Key words: Prostate neoplasms; Magnetic resonance imaging; Pathology

The Utility of Diffusion Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) Values in Discriminating Between Prostate Cancer and Normal Tissue.

SummaryBackgroundThe aim of this study was to investigate the utility of diffusion weighted imaging (DWI) using Apparent Diffusion Coefficient (ADC) values in discriminating between patients with tumors and normal prostate tissue before the initial systematic core biopsy. The relationship between histological grade of prostate cancer and ADC values in the peripheral zone was also investigated.Material/MethodsOur study included 62 patients who underwent magnetic resonance imaging (MRI) of the pelvis. The examinations were performed in T1-, T2-weighted, DWI and T1 after dynamic contrast administration sequences. In all patients there were abnormal foci within the peripheral zone determined in DWI/ADC. ADC values were compared with the Gleason score (GS) after core needle biopsy (CNB) in patients with low, medium and high stage tumors.ResultsWithin the examined group of patients, ADC was statistically higher for normal tissue than for cancerous tissue (p=0.00). Mean ADC values for patients with low, intermediate and high GS were 0.85±0.03, 0.72±0.03, and 0.61±0.04, respectively.ConclusionsDWI/ADC is useful in differentiating high-risk patients from those at low and intermediate risk, since there is a significant correlation between ADC values determined in patients included in three different groups according to their Gleason score. This information may be helpful in the assessment of prostate cancer aggressiveness.

Prostate MRI: Who, when, and how? Report from a UK consensus meeting

The current pathway for men suspected of having prostate cancer [transrectal biopsy, followed in some cases by magnetic resonance imaging (MRI) for staging] results in over-diagnosis of insignificant tumours, and systematically misses disease in the anterior prostate. Multiparametric MRI has the potential to change this pathway, and if performed before biopsy, might enable the exclusion of significant disease in some men without biopsy, targeted biopsy in others, and improvements in the performance of active surveillance. For the potential benefits to be realized, the setting of standards is vital. This article summarizes the outcome of a meeting of UK radiologists, at which a consensus was achieved on (1) the indications for MRI, (2) the conduct of the scan, (3) a method and template for reporting, and (4) minimum standards for radiologists.

Assessment of Prostate Cancer Aggressiveness Using Dynamic Contrast-enhanced Magnetic Resonance Imaging at 3 T

BackgroundA challenge in the diagnosis of prostate cancer (PCa) is the accurate assessment of aggressiveness. ObjectiveTo validate the performance of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate at 3 tesla (T) for the assessment of PCa aggressiveness, with prostatectomy specimens as the reference standard. Design, settings, and participantsA total of 45 patients with PCa scheduled for prostatectomy were included. This study was approved by the institutional review board; the need for informed consent was waived. Outcome measurements and statistical analysisSubjects underwent a clinical MRI protocol including DCE-MRI. Blinded to DCE-images, PCa was indicated on T2-weighted images based on histopathology results from prostatectomy specimens with the use of anatomical landmarks for the precise localization of the tumor. PCa was classified as low-, intermediate-, or high-grade, according to Gleason score. DCE-images were used as an overlay on T2-weighted images; mean and quartile values from semi-quantitative and pharmacokinetic model parameters were extracted per tumor region. Statistical analysis included Spearman's ρ, the Kruskal-Wallis test, and a receiver operating characteristics (ROC) analysis. Results and limitationsSignificant differences were seen for the mean and 75th percentile (p75) values of wash-in (p = 0.024 and p = 0.017, respectively), mean wash-out (p = 0.044), and p75 of transfer constant (Ktrans) (p = 0.035), all between low-grade and high-grade PCa in the peripheral zone. ROC analysis revealed the best discriminating performance between low-grade versus intermediate-grade plus high-grade PCa in the peripheral zone for p75 of wash-in, Ktrans, and rate constant (Kep) (area under the curve: 0.72). Due to a limited number of tumors in the transition zone, a definitive conclusion for this region of the prostate could not be drawn. ConclusionsQuantitative parameters (Ktrans and Kep) and semi-quantitative parameters (wash-in and wash-out) derived from DCE-MRI at 3 T have the potential to assess the aggressiveness of PCa in the peripheral zone. P75 of wash-in, Ktrans, and Kep offer the best possibility to discriminate low-grade from intermediate-grade plus high-grade PCa.

Interpatient Variation in Normal Peripheral Zone Apparent Diffusion Coefficient: Effect on the Prediction of Prostate Cancer Aggressiveness

To determine the interpatient variability of prostate peripheral zone (PZ) apparent diffusion coefficient (ADC) and its effect on the assessment of prostate cancer aggressiveness. The requirement for institutional review board approval was waived. Intra- and interpatient variation of PZ ADCs was determined by means of repeated measurements of normal ADCs at three magnetic resonance (MR) examinations in a retrospective cohort of 10 consecutive patients who had high prostate-specific antigen levels and negative findings at transrectal ultrasonographically-guided biopsy. In these patients, no signs of PZ cancer were found at all three MR imaging sessions. The effect of interpatient variation on the assessment of prostate cancer aggressiveness was examined in a second retrospective cohort of 51 patients with PZ prostate cancer. Whole-mount step-section pathologic evaluation served as reference standard for placement of regions of interest on tumors and normal PZ. Repeated-measures analysis of variance was used to determine the significance of the interpatient variations in ADCs. Linear logistic regression was used to assess whether incorporating normal PZ ADCs improves the prediction of cancer aggressiveness. Analysis of variance revealed that interpatient variability (1.2-2.0×10(-3) mm2/sec) was significantly larger than measurement variability (0.068×10(-3) mm2/sec±0.027 [standard deviation]) (P=.0058). Stand-alone tumor ADCs showed an area under the receiver operating characteristic curve (AUC) of 0.91 for discriminating low-grade versus high-grade tumors. Incorporating normal PZ ADC significantly improved the AUC to 0.96 (P=.0401). PZ ADCs show significant interpatient variation, which has a substantial effect on the prediction of prostate cancer aggressiveness. Correcting this effect results in a significant increase in diagnostic accuracy.

Prostate Cancer Aggressiveness: In Vivo Assessment of MR Spectroscopy and Diffusion-weighted Imaging at 3 T

To determine the individual and combined performance of magnetic resonance (MR) spectroscopic imaging and diffusion-weighted (DW) imaging at 3 T in the in vivo assessment of prostate cancer aggressiveness by using histopathologically defined regions of interest on radical prostatectomy specimens to define the prostate cancer regions to be investigated. The local institutional ethics review board approved this retrospective study and waived the informed consent requirement. Fifty-four patients with biopsy-proved prostate cancer underwent clinical MR spectroscopic imaging followed by prostatectomy. Guided by the histopathologic map, all spectroscopy voxels that contained tumor tissue were selected, and metabolite ratios (choline [Cho] plus creatine [Cr]-to-citrate [Cit] and Cho/Cr ratios) were derived. For each spectroscopic voxel, 25th percentile apparent diffusion coefficient (ADC) of the region corresponding to that voxel was determined, representing the most aberrant tumor part on the ADC map, which was often smaller than spectroscopic imaging voxels. Maximum metabolic ratios and minimum 25th percentile ADC of each tumor were related to tumor aggressiveness and were used to differentiate aggressiveness classes. A logistic regression model (LRM) was used to combine data from both modalities. Significant correlation was found between aggressiveness classes and maximum Cho+Cr/Cit ratio (ρ=0.36), maximum Cho/Cr ratio (ρ=0.35), and minimum 25th percentile ADC (ρ=-0.63) in the peripheral zone (PZ). In the transition zone (TZ), the correlation was significant for only Cho+Cr/Cit and Cho/Cr ratios (ρ=0.58 and ρ=0.60, respectively). For differentiation between aggressiveness classes, LRM use did not result in significantly improved differentiation over any individual variables. These findings enabled confirmation that MR spectroscopic imaging and DW imaging offer potential for in vivo noninvasive assessment of prostate cancer aggressiveness, and both modalities have comparable performance. The combination did not result in better performance. Nonetheless, the better performances of metabolite ratios in the TZ and of ADCs in the PZ suggest that they have complementary value.

Diffusion-Weighted and Dynamic Contrast-Enhanced MRI of Prostate Cancer: Correlation of Quantitative MR Parameters With Gleason Score and Tumor Angiogenesis

The objective of our study was to investigate whether quantitative parameters derived from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) correlate with Gleason score and angiogenesis of prostate cancer. Seventy-three patients who underwent preoperative MRI and radical prostatectomy were included in our study. A radiologist and pathologist located the dominant tumor on the MR images based on histopathologic correlation. For each dominant tumor, the apparent diffusion coefficient (ADC) value and quantitative DCE-MRI parameters (i.e., contrast agent transfer rate between blood and tissue [K(trans)], extravascular extracellular fractional volume [v(e)], contrast agent backflux rate constant [k(ep)], and blood plasma fractional volume on a voxel-by-voxel basis [v(p)]) were calculated and the Gleason score was recorded. The mean blood vessel count, mean vessel area fraction, and vascular endothelial growth factor (VEGF) expression of the dominant tumor were determined using CD31, CD34, and VEGF antibody stains. Spearman correlation analysis between MR and histopathologic parameters was conducted. The mean tumor diameter was 15.2 mm (range, 5-28 mm). Of the 73 prostate cancer tumors, five (6.8%) had a Gleason score of 6, 46 (63%) had a Gleason score of 7, and 22 (30.1%) had a Gleason score of greater than 7. ADC values showed a moderate negative correlation with Gleason score (r = -0.376, p = 0.001) but did not correlate with tumor angiogenesis parameters. Quantitative DCE-MRI parameters did not show a significant correlation with Gleason score or VEGF expression (p > 0.05). Mean blood vessel count and mean vessel area fraction parameters estimated from prostate cancer positively correlated with k(ep) (r = 0.440 and 0.453, respectively; p = 0.001 for both). There is a moderate correlation between ADC values and Gleason score and between k(ep) and microvessel density of prostate cancer. Although the strength of the correlations is insufficient for immediate diagnostic utility, these results warrant further investigation on the potential of multiparametric MRI to facilitate noninvasive assessment of prostate cancer aggressiveness and angiogenesis.

In Vivo Assessment of Prostate Cancer Aggressiveness Using Magnetic Resonance Spectroscopic Imaging at 3 T with an Endorectal Coil

BackgroundOne of the most important clinical challenges in prostate cancer (PCa) management is an in vivo assessment of cancer aggressiveness. ObjectiveTo validate the performance of magnetic resonance (MR) spectroscopic imaging (MRSI) of the prostate at 3 T for the purpose of assessing tumour aggressiveness based on the ratio of choline plus creatine to citrate (Cho+Cr/Cit) and of choline to creatine (Cho/Cr), using the Gleason score of the radical prostatectomy (RP) specimen as the gold standard. Design, setting, and participantsA total of 43 biopsy-proven PCa patients with 53 clinically relevant tumour foci were retrospectively included in this study. MeasurementsPatients underwent MR imaging and MRSI examination followed by RP. From MRSI, all spectroscopy voxels containing tumour were selected by a radiologist guided by the prostatectomy histopathology map only. For each tumour, two spectroscopists determined the maximum Cho+Cr/Cit, Cho/Cr, and malignancy rating using a standardised threshold approach, incorporating both metabolic ratios. The maximum Cho+Cr/Cit, Cho/Cr, and malignancy ratings showed a relation to tumour aggressiveness and so were used to differentiate among tumour aggressiveness classes. Results and limitationsThe maximum Cho+Cr/Cit ratio, maximum Cho/Cr ratio, and malignancy rating of a standardised threshold approach separated low-grade from higher-grade tumours, with areas under the receiver operating characteristic (ROC) curves of 0.70, 0.74, and 0.78, respectively. ConclusionsMRSI offers possibilities for an in vivo, noninvasive assessment of PCa aggressiveness. The combination of the different metabolite ratios was used with promising results for discrimination among different aggressiveness classes.

Contrast-Enhanced Harmonic Ultrasonography for the Assessment of Prostate Cancer Aggressiveness: a Preliminary Study

ObjectiveTo determine whether contrast-enhanced harmonic ultrasonography can be used to predict the aggressiveness of prostate cancer.Materials and MethodsContrast-enhanced harmonic ultrasonography was performed in 103 patients suspected of prostate cancer before biopsy. Time intensity curves were reconstructed for systematic biopsy sites and sonographic abnormalities. The characteristics of the curves were described using hemodynamic indices including arrival time (AT), time-to-peak (TTP), and peak intensity (PI). The differences of hemodynamic indices between high-grade and low-grade cancer were analyzed and the correlations between the hemodynamic indices and biopsy Gleason score were studied.ResultsProstate cancer was detected in 41 of 103 patients and there were significant differences in the hemodynamic indices between the biopsy sites of the non-malignant patients and prostate cancer lesions (p < 0.05). The prostate biopsies revealed 154 prostate cancer lesions, including 31 low-grade lesions and 123 high-grade lesions. The hemodynamic indices AT and TTP of high-grade tumors were significantly shorter than those of low-grade tumors (p = 0.001, 0.002). In addition, high-grade peripheral zone (PZ) tumors had higher PI than low-grade PZ tumors (p = 0.009). The PZ prostate cancer Gleason score correlated with PI, AT and TTP, with Spearman correlation coefficients of 0.223, -0.335, and -0.351, respectively (p = 0.013, < 0.001 and < 0.001).ConclusionContrast-enhanced ultrasound measurements of hemodynamic indices correlate with the prostate cancer Gleason score.