Prediction of biochemical recurrence following radical prostatectomy in men with prostate cancer by diffusion-weighted magnetic resonance imaging: initial results

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study

INTRODUCTION

To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low- and intermediate-risk prostate cancer (PCa) treated with stereotactic ablative radiotherapy (SABR).

METHODS

Retrospective evaluation was performed for 30 patients using pre-treatment multi-parametric MR image datasets between 2017 and 2021. MR-based mean- and minimum apparent diffusion coefficients (ADCmean, ADCmin) were calculated for the intraprostatic dominant lesion. Therapeutic response was assessed using PSA levels. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis. Statistics performed with a significance level of p ≤ 0.05.

RESULTS

No biochemical relapse was detected after a median follow-up of twenty-three months (range: 3-50), with a median PSA of 0.01 ng/ml (range: 0.006-2.8) at the last examination. Significant differences were observed between the pre-treatment ADCmean, ADCmin parameters, and the group averages of patients with low and high 1-year-PSA measurements (p < 0.0001, p < 0.0001). In prediction, the random forest (RF) model outperformed the decision tree (DT) and support vector machine (SVM) models by yielding area under the curves (AUC), with 0.722, 0.685, and 0.5, respectively.

CONCLUSION

Our findings suggest that pre-treatment MR diffusion data may predict therapeutic response using the novel approach of machine learning in PCa patients treated with SABR.

IMPLICATIONS FOR PRACTICE

Clinicians shall measure and implement the evaluation of the suggested parameters (ADCmin, ADCmean) to provide the most accurate therapy for the patient.

Amide proton transfer imaging has added value for predicting extraprostatic extension in prostate cancer patients

Background

Prostate cancer invades the capsule is a key factor in selecting appropriate treatment methods. Accurate preoperative prediction of extraprostatic extension (EPE) can help achieve precise selection of treatment plans.

Purpose

The aim of this study is to verify the diagnostic efficacy of tumor size, length of capsular contact (LCC), apparent diffusion coefficient (ADC), and Amide proton transfer (APT) value in predicting EPE. Additionally, the study aims to investigate the potential additional value of APT for predicting EPE.

Method

This study include 47 tumor organ confined patients (age, 64.16 ± 9.18) and 50 EPE patients (age, 61.51 ± 8.82). The difference of tumor size, LCC, ADC and APT value between groups were compared. Binary logistic regression was used to screen the EPE predictors. The receiver operator characteristic curve analysis was performed to assess the diagnostic performance of variables for predicting EPE. The diagnostic efficacy of combined models (model I: ADC+LCC+tumor size; model II: APT+LCC+tumor size; and model III: APT +ADC+LCC+tumor size) were also analyzed.

Results

APT, ADC, tumor size and the LCC were independent predictors of EPE. The area under the curve (AUC) of APT, ADC, tumor size and the LCC were 0.752, 0.665, 0.700 and 0.756, respectively. The AUC of model I, model II, and model III were 0.803, 0.845 and 0.869, respectively. The cutoff value of APT, ADC, tumor size and the LCC were 3.65%, 0.97×10-3mm2/s, 17.30mm and 10.78mm, respectively. The sensitivity/specificity of APT, ADC, tumor size and the LCC were 76%/89.4.0%, 80%/59.6%, 54%/78.9%, 72%/66%, respectively. The sensitivity/specificity of model I, Model II and Model III were 74%/72.3%, 82%/72.5% and 84%/80.9%, respectively.

Data conclusion

Amide proton transfer imaging has added value for predicting EPE. The combination model of APT balanced the sensitivity and specificity.

The impact of the apparent diffusion coefficient for the early prediction of the treatment response after definitive radiotherapy in prostate cancer patients

PURPOSE

We assessed early changes in apparent diffusion coefficient (ADC) and serum prostate specific antigen (PSA) values after definitive radiotherapy (RT) without androgen deprivation treatment in low- and intermediate-risk prostate cancer (PC) patients.

MATERIALS AND METHODS

The clinical data and ADC parameters of 229 PC patients were retrospectively evaluated. Pre-treatment and post-treatment serum PSA and primary tumor ADC values were calculated. Post-treatment DW-MRI was performed median 4.1 months after completion of definitive RT. The prognostic factors predicting freedom from biochemical failure (FFBF) and progression-free survival (PFS) were analyzed using univariable and multivariable analyses.

RESULTS

With a median follow-up time of 80.8 months, the 5-year FFBF and PFS rates were 95.9% and 89.3%, respectively. Eleven patients (4.8%) had PSA relapse, with a median of 34.4 months after the completion of RT. A statistically significant difference in post-treatment ADC values was noted between patients with and without recurrence (0.94 ± 0.07 vs. 1.10 ± 0.20 × 10^-3 mm²/sec; p < 0.001). Patients with a Gleason score (GS) of 6 and low-risk disease had significantly higher post-treatment tumor ADC and PSA levels than patients with a GS of 7 and intermediate-risk disease. The 5-year FFBF rate in patients with tumor ADC ≤ 0.96 × 10^-3 mm²/sec was significantly lower than patients with tumor ADC > 0.96 × 10^-3 mm²/sec (85.5% vs. 100; p < 0.001). In the multivariable analysis, a lower ADC value, GS 4 + 3 and intermediate-risk disease were independent predictors of worse FFBF. In the multivariate analysis, a lower post-treatment ADC value and a GS of 4+3 were significant prognostic factors for a lower PFS.

CONCLUSION

These findings suggest that the post-treatment tumor ADC value could be used for early treatment response evaluation after definitive RT in PC patients.

Can Pre-treatment Quantitative Multi-parametric MRI Predict the Outcome of Radiotherapy in Patients with Prostate Cancer?

RATIONALE AND OBJECTIVES

To investigate whether pre-treatment quantitative multiparametric MRI can predict biochemical outcome of prostate cancer (PCa) patients treated with primary radiotherapy (RT).

MATERIALS AND METHODS

Fifty-one patients with biopsy confirmed PCa underwent prostate multiparametric MRI on 3T MR scanner prior to RT. Thirty-seven men (73%) were treated with external beam RT alone, 12 men (24%) were treated with brachytherapy monotherapy, and two men (4%) were treated with external beam RT with brachytherapy boost. The index lesion was outlined by a radiologist and quantitative apparent diffusion coefficient (ADC), T2 and DCE parameters were measured. Biochemical failure was defined using the Phoenix criteria.

RESULTS

After a median follow-up of 65 months, seven patients had biochemical failure. ADC had an area under the receiver operating characteristic curve of 0.71 for predicting RT outcome with significantly lower ADC (0.78 ± 0.17 vs 0.96 ± 0.26 µm²/ms, p = 0.04) of the index lesion in men with biochemical failure. Ideal ADC cutoff point (Youdens index) was 0.96 µm²/ms which had a sensitivity of 100% and specificity of 48% for predicting biochemical failure. Kaplan-Meier analysis showed that lower ADC values were associated with significantly lower freedom from biochemical failure (FFBF, p = 0.03, no failures out of 20 men if ADC ≥ 0.96 µm²/ms; seven of 31 with failures if ADC < 0.96 µm²/ms). On multivariable analysis, ADC was associated with FFBF (HR 0.96 per increase in ADC of 0.01 um²/ms [95% CI, 0.92-1.00]; p = 0.042) after accounting for National Comprehensive Cancer Network risk category (p = 0.064) and receipt of androgen deprivation therapy (p = 0.141). Quantitative T2 and DCE parameters were not associated with biochemical outcome.

CONCLUSION

Our results suggest that quantitative ADC values of the index lesion may predict biochemical failure following primary radiotherapy in patients with PCa. Lower ADC values were associated with inferior biochemical control.

The prognostic value of mean apparent diffusion coefficient measured with diffusion-weighted magnetic resonance image in patients with prostate cancer treated with definitive radiotherapy

PURPOSE

To assess the correlation between initial tumor apparent diffusion coefficient (ADC) values and clinicopathological parameters in prostate cancer (PCa) patients treated with definitive radiotherapy (RT). Additionally, the prognostic factors for freedom from biochemical failure (FFBF) and progression-free survival (PFS) in this patient cohort were analyzed.

MATERIALS AND METHODS

The clinical data of 503 patients with biopsy-confirmed PCa were evaluated retrospectively. All patients had clearly evident tumors on diffusion-weighted magnetic resonance imaging (DW-MRI) for ADC values. Univariable and multivariable analyses were used to determine prognostic factors for FFBF and PFS.

RESULTS

The median follow-up was 72.9 months. The 5-year FFBF and PFS rates were 93.2% and 86.2%, respectively. Significantly lower ADC values were found in patients with a high PSA level; advanced clinical stage; higher ISUP score, and higher risk group than their counterparts. Receiver operating characteristic (ROC) curve analysis revealed an ADC cut-off value of 0.737 × 10^-3 mm²/sec for tumor recurrence. Patients who progressed had a lower mean ADC value than those who did not (0.712±0.158 vs. 1.365±0.227 × 10^-3 mm²/sec; p<0.001). There was a significant difference in 5-year FFBF (96.3% vs. 90%; p<0.001) and PFSrates (83.8% vs. 73.5%; p=0.002) between patients with higher and lower mean ADC values. The FFBF and PFS were found to be correlated with tumor ADC value and ISUP grades in multivariable analysis. Additionally, older age was found to be a significant predictor of worse PFS.

CONCLUSIONS

Lower ADC values were found in patients with high-risk characteristics such as a high serum PSA level, stage or grade of tumor, or high-risk disease, implying that ADC values could be used to predict prognosis. Lower ADC values and higher ISUP grades were associated with an increased risk of BF and progression, implying that treatment intensification may be required in these patients.

Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities

Advances in our understanding of the role of magnetic resonance imaging (MRI) for the detection of prostate cancer have enabled its integration into clinical routines in the past two decades. The Prostate Imaging Reporting and Data System (PI-RADS) is an established imaging-based scoring system that scores the probability of clinically significant prostate cancer on MRI to guide management. Image fusion technology allows one to combine the superior soft tissue contrast resolution of MRI, with real-time anatomical depiction using ultrasound or computed tomography. This allows the accurate mapping of prostate cancer for targeted biopsy and treatment. Machine learning provides vast opportunities for automated organ and lesion depiction that could increase the reproducibility of PI-RADS categorisation, and improve co-registration across imaging modalities to enhance diagnostic and treatment methods that can then be individualised based on clinical risk of malignancy. In this article, we provide a comprehensive and contemporary review of advancements, and share insights into new opportunities in this field.

The utility of ADC parameters in the diagnosis of clinically significant prostate cancer by 3.0-Tesla diffusion-weighted magnetic resonance imaging

Purpose

This study has focused on investigating the relationship between the exponential apparent diffusion coefficient (exp-ADC), selective apparent diffusion coefficient (sel-ADC) values, the ADC ratio (ADCr), and prostate cancer aggressiveness with transrectal ultrasound-guided prostate biopsy in patients with prostate cancer.

Material and methods

All patients underwent a multiparametric magnetic resonance imaging (mpMRI) including tri-planar T2-weighted (T2W), dynamic contrast-enhanced (DCE), diffusion-weighted sequences using a 3.0-Tesla MR scanner (Skyra, Siemens Medical Systems, Germany) with a dedicated 18-channel body coil and a spine coil underneath the pelvis, with the patient in the supine position. Exp-ADC, sel-ADC, and ADCr of defined lesions were evaluated using region-of-interest-based measurements. Exp-ADC, sel-ADC, and ADCr were correlated with the Gleason score obtained through transrectal ultrasound-guided biopsy.

Results

Patients were divided into 2 groups. Group I is Gleason score ≥ 3 + 4, group II is Gleason score = 6. Sel-ADC and exp-ADC were statistically significant between 2 groups (0.014 and 0.012, respectively). However, the ADCr difference between nonclinical significant prostate cancer from clinically significant prostate cancer was not significant (p = 0.09).

Conclusions

This study is the first to evaluate exp-ADC and sel-ADC values of prostate carcinoma with ADCr. One limitation of this study might be the limited number of patients. Exp-ADC and sel-ADC values in prostate MRI imaging improved the specificity, accuracy, and area under the curve (AUC) for detecting clinically relevant prostate carcinoma. Adding exp-ADC and sel-ADC values to ADCr can be used to increase the diagnostic accuracy of DWI.

Rectal gas-induced susceptibility artefacts on prostate diffusion-weighted MRI with epi read-out at 3.0 T: does a preparatory micro-enema improve image quality?

Purpose

To assess whether the application of a preparatory micro-enema reduces gas-induced susceptibility artefacts on diffusion-weighted MRI of the prostate.

Methods

114 consecutive patients who received multiparametric 3 T MRI of the prostate at our institution were retrospectively enrolled. 63 patients self-administered a preparatory micro-enema prior to imaging, and 51 patients underwent MRI without bowel preparation. Two blinded readers independently reviewed the diffusion-weighted sequences regarding gas-induced artefacts. The presence/severity of artefacts was scored ranging from 0 (no artefact) to 3 (severe artefact). A score ≥ 2 was considered a clinically relevant artefact. Maximum rectal width at the level of the prostate was correlated with the administration of a micro-enema. Scores were compared between the scans performed with and without bowel preparation using univariable and multivariable logistic regression, taking into account potential confounding factors (age and prostate volume).

Results

Significantly less artefacts were found on diffusion-weighted sequences after the administration of a micro-enema shortly prior to MR imaging. Clinically relevant artefacts were found in 10% in the patient group after enema, in 41% without enema. If present, artefacts were also significantly less severe. Mean severity score was 0.3 (enema administered) and 1.2 (no enema), and odds ratio was 0.137 (p < 0.0001) in univariable ordinal logistic regression. Inter-observer agreement was excellent (κ 0.801).

Conclusion

The use of a preparatory micro-enema prior to 3 T multiparametric prostate MRI significantly reduces both the incidence and severity of gas-induced artefacts on diffusion-weighted sequences and thus improves image quality.

Electronic supplementary material

The online version of this article (10.1007/s00261-020-02600-9) contains supplementary material, which is available to authorized users.

The significance of the visible tumor on preoperative magnetic resonance imaging in localized prostate cancer

Objectives

We investigated the relationship between tumor characteristics and visible tumors on magnetic resonance imaging (MRI) and examined the prognosis of tumor detection on MRI compared with no tumor detection in localized prostate cancer.

Materials and methods

We reviewed 214 patients with pT2N0M0 prostate cancer who underwent radical prostatectomy between January 2009 and December 2016. All the patients underwent MRI preoperatively. The patients were divided into 2 groups postoperatively: no visible tumor on the MRI group (n = 96, 44.9%) and visible tumor on the MRI group (n = 118, 55.1%). The visible tumor was defined as Prostate Imaging Reporting and Data System, version 2 Grade ≥ 3 on MRI. Age, prostate-specific antigen, prostate volume, positive surgical margin (PSM), lymphovascular invasion, and biochemical recurrence (BCR) were compared between the 2 groups. We also assessed the relationship between visible tumors on MRI and oncologic characteristics.

Results

The visible tumor on the MRI group showed a higher Gleason score ≥4 + 3 [45.8% versus (vs.) 17.7%], high frequency of postoperative PSMs (28.8% vs. 16.7%), and higher BCR rate (17.8% vs. 7.3%) than the no visible tumor on the MRI group. The Kaplan–Meier analysis for BCR-free survival also showed a significant difference (P = 0.006). In multivariate Cox regression analysis, the detection of tumors on MRI was associated with a higher BCR risk [hazard ratio: 3.35; 95% confidence interval (CI): 1.36-8.27; P = 0.009]. We found a positive association between visible tumors on MRI and primary Gleason pattern of ≥4 (odds ratio: 4.31; 95% CI: 2.21–8.40; P < 0.001).

Conclusions

In localized prostate cancer, BCR was significantly more frequent when the tumor was detected on MRI, and a visible tumor on MRI was associated with the Gleason score. Therefore, attention should be paid to the possibility of high-grade prostate cancer when a tumor is detected on MRI before radical prostatectomy, and active follow-up may be needed postoperatively.

Clinical MR Biomarkers

Non-invasive magnetic resonance imaging (MRI) techniques are increasingly applied in the clinic with a fast growing body of evidence regarding its value for clinical decision making. In contrast to biochemical or histological markers, the key advantages of imaging biomarkers are the non-invasive nature and the spatial and temporal resolution of these approaches. The following chapter focuses on clinical applications of novel MR biomarkers in humans with a strong focus on oncologic diseases. These include both clinically established biomarkers (part 1-4) and novel MRI techniques that recently demonstrated high potential for clinical utility (part 5-7).

Prognostic Significance for Long-Term Outcomes Following Radical Prostatectomy in Men with Prostate Cancer: Evaluation with Prostate Imaging Reporting and Data System Version 2

Objective

To retrospectively determine whether the use of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) helps predict long-term outcomes for prostate cancer (PCa) patients following radical prostatectomy (RP).

Materials and Methods

A total of 166 patients with localized PCa evaluated with multiparametric magnetic resonance imaging (mpMRI) at 3T before RP were enrolled. Three groups were created based on PI-RADS v2 score used to predict clinical outcomes: group A, ≥ 3; group B, ≥ 4; group C, 5. We calculated biochemical recurrence-free survival (RFS) and progression-free survival (PFS). Cox proportion hazards models were used to identify variables predictive of biochemical recurrence and disease progression.

Results

During a median follow-up of 9.1 years, biochemical recurrence occurred in 67 patients (40.4%) and disease progression occurred in 55 patients (33.1%). In all groups, 10-year RFS and 10-year PFS were significantly lower for PI-RADS scores ≥ 3, ≥ 4 and 5 than for score < 3, < 4 and < 5 (p <0.05), respectively. In multivariate analysis, PI-RADS score ≥ 3 and score 5 were significant independent risk marker for biochemical recurrence (hazard ratio [HR] = 5.58, p = 0.018; HR = 1.75, p = 0.033) and disease progression (HR = 3.99, p = 0.047; HR = 2.31, p = 0.040). Moderate inter-observer agreement was seen for PI-RADS scoring.

Conclusion

PI-RADS v2 may be used to predict long-term outcomes following RP in PCa.

Correlation of SUVmax and Apparent Diffusion Coefficient Values Detected by Ga-68 PSMA PET/MRI in Primary Prostate Lesions and Their Significance in Lymph Node Metastasis: Preliminary Results of an On-going Study

Objectives:

Gallium-68 (Ga-68) prostate specific membrane antigen (PSMA) positron emission tomography (PET) has been shown to be more accurate than multiparametric prostate magnetic resonance imaging (MRI) in detection of primary prostate lesions. Using hybrid PET/MRI we aim to detect the correlation between SUV_max and apparent diffusion coefficient (ADC) in primary prostate lesions and to assess their prognostic value in detection of lymph node (LN) metastasis.

Methods:

Twenty-six patients, who were diagnosed as having prostate cancer with biopsy and underwent Ga-68 PSMA PET/MRI together with biparametric prostate MRI (bpMRI) were included. SUV_max, SUV_mean and ADC were recorded for index lesions drawing a region of interest (ROI) of 1 cm² around the pixel with the highest SUV_max (ROI-1) and another ROI following borders of prostate tumor detected by bpMRI (ROI-2). Presence of LN metastasis was recorded according to PSMA PET/MRI.

Results:

SUV_max was inversely correlated with ADC (ROI-1: p=0.010; ROI-2: p=0.017 for b=800). SUV_max and SUV_means were both higher in patients with LN metastasis and ADC was lower in patients with LN metastasis for ROI-1. SUV_max cut-off value of 19.8 for ROI-1 and 20.9 for ROI-2 had sensitivity and specificity of 77.8% and 76.5%, respectively for detection of LN metastasis, whereas ADC (b=800) cut-off value of 0.92x10^-3 mm²/s had sensitivity and specificity of 87.5% and 76.5%, respectively. SUV_max/ADC (b=800) ratio increased the sensitivity and specificity to 100% and 82.4%, respectively.

Conclusion:

SUV and ADC values are inversely correlated in primary prostate lesions and the combined use of both values increases the diagnostic accuracy of hybrid PET/MRI in the detection of primary prostate lesions.

Effects of the addition of quantitative apparent diffusion coefficient data on the diagnostic performance of the PI-RADS v2 scoring system to detect clinically significant prostate cancer

PURPOSE

To evaluate the impact of the addition of quantitative apparent diffusion coefficient (ADC) data into the diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system to predict clinically significant prostate cancer (CSPCa).

METHODS

We retrospectively included 91 consecutive patients who underwent prostate multiparametric magnetic resonance imaging (mp-MRI) and histopathological evaluation. Mp-MRI images were reported by the PI-RADSv2 scoring system and patients were divided into groups considering the likelihood of CSPCa. ADC value and ratio were obtained. Findings were correlated with histopathological data.

RESULTS

CSPCa was found in 41.8% of cases (n = 38). PI-RADSv2 score 3-5 yielded a sensitivity of 97.4% (95% confidence intervals 86.5-99.5), a specificity of 50.9% (37.9-63.9), and AUC of 0.74 (0.67-0.81) to predict CSPCa. ADC value < 750 µm²/s and an ADC ratio < 0.62 were the most accurate thresholds for differentiation of CSPCa, with AUC of 0.81 and 0.76, respectively. Combined PI-RADSv2 score 3-5 and ADC value < 750 µm²/s yielded a specificity of 84.9 (72.9-92.2), sensitivity of 70.3 (54.2-82.5), and AUC of 0.77 (0.68-0.86). Combined PI-RADSv2 score 3-5 and ADC ratio < 0.62 yielded a specificity of 86.5 (74.7-93.3), sensitivity of was 64.9 (48.8-78.2), and AUC of 0.75 (0.66-0.84).

CONCLUSION

Quantitative ADC data might not be beneficial to be used routinely in mp-MR imaging as criteria to detect clinically significant lesions due to the reduced sensitivity. Instead, when prostate lesions present a PI-RADSv2 score ≥ 3, additional quantitative ADC criteria can be helpful to increase the PI-RADS score specificity.

Multiparametric MRI and radiomics in prostate cancer: a review

Multiparametric MRI (mpMRI) is an imaging modality that combines anatomical MR imaging with one or more functional MRI sequences. It has become a versatile tool for detecting and characterising prostate cancer (PCa). The traditional role of mpMRI was confined to PCa staging, but due to the advanced imaging techniques, its role has expanded to various stages in clinical practises including tumour detection, disease monitor during active surveillance and sequential imaging for patient follow-up. Meanwhile, with the growing speed of data generation and the increasing volume of imaging data, it is highly demanded to apply computerised methods to process mpMRI data and extract useful information. Hence quantitative analysis for imaging data using radiomics has become an emerging paradigm. The application of radiomics approaches in prostate cancer has not only enabled automatic localisation of the disease but also provided a non-invasive solution to assess tumour biology (e.g. aggressiveness and the presence of hypoxia). This article reviews mpMRI and its expanding role in PCa detection, staging and patient management. Following that, an overview of prostate radiomics will be provided, with a special focus on its current applications as well as its future directions.

Amide proton transfer imaging to predict tumor response to neoadjuvant chemotherapy in locally advanced rectal cancer

BACKGROUND AND AIM

The amount of proteins and peptides can be estimated with amide proton transfer (APT) imaging. Previous studies demonstrated the usefulness of APT imaging to predict tumor malignancy. We determined whether APT imaging can predict the tumor response to neoadjuvant chemotherapy (NAC) in patients with locally advanced rectal cancer (LARC).

METHODS

Seventeen patients with LARC who underwent a pretherapeutic magnetic resonance examination including APT imaging and NAC (at least two courses) were enrolled. The APT-weighted imaging (WI) signal intensity (SI) (%) was defined as magnetization transfer ratio asymmetry (MTR_asym ) at the offset of 3.5 ppm. Each tumor was histologically evaluated for the degree of degeneration and necrosis and then classified as one of five histological Grades (0, none; 1a, less than 1/3; 1b, 1/3 to 2/3; 2, more than 2/3; 3, all). We compared the mean APTWI SIs of the tumors between the Grade 0/1a/1b (low-response group) and Grade 2/3 (high-response group) by Student's t-test. We used receiver operating characteristics curves to determine the diagnostic performance of the APTWI SI for predicting the tumor response.

RESULTS

The mean APTWI SI of the low-response group (n = 12; 3.05 ± 1.61%) was significantly higher than that of the high-response group (n = 5; 1.14 ± 1.13%) (P = 0.029). The area under the curve for predicting the tumor response using the APTWI SI was 0.87. When ≥2.75% was used as an indicator of low-response status, 75% sensitivity and 100% specificity of the APTWI SI were obtained.

CONCLUSION

Pretherapeutic APT imaging can predict the tumor response to NAC in patients with LARC.

Correlation of apparent diffusion coefficient ratio on 3.0 T MRI with prostate cancer Gleason score

•

ADC_ratio is a reliable and reproducible tool in quantification of diffusion restriction for clinically significant PCa foci.

•

Comparing an experienced and a new MRI reader, Inter-reader reliability in the calculation of ADC_ratio was excellent.

•

ADC_ratio has potential to replace the current practice of visual analysis of ADC_tumour reduction, and provide an objective tool.

Introduction

The purpose was to investigate the usefulness of ADC_ratio on Diffusion MRI to discriminate between benign and malignant lesions of Prostate.

Methods

Images of patients who underwent in-gantry MRI guided prostate lesion biopsy were retrospectively analyzed. Prostate Cancers with 20% or more Gleason score (GS) pattern 3 + 3 = 6 in each core or any volume of higher Gleason score pattern were included. ADC_ratio was calculated by two reviewers for each lesion. The ADC_ratio was calculated for each lesion by dividing the lowest ADC value in a lesion and highest ADC value in normal prostate in peripheral zone (PZ). ADC_ratio values were compared with the biopsy result. Data was analysed using independent samples T-test, Spearman correlation, intra-class correlation coefficient (ICC) and Receiver operating characteristic (ROC) curve.

Results

45 lesions in 33 patients were analyzed. 12 lesions were in transitional zone (TZ) and 33 in perpheral zone PZ. All lesions demonstrated an ADC_ratio of 0.45 or lower. GS demonstrated a negative correlation with both the ADC value and ADC_ratio. However, ADC_ratio (p < 0.001) demonstrated a stronger correlation compared to ADC value alone (p = 0.014). There was no significant statistical difference between GS 3 + 4 and GS 4 + 3 mean ADC_tumour value (p = 0.167). However when using ADC_ratio, there was a significant difference (p = 0.032). ROC curve analysis demonstrated an area under the curve of 0.83 using ADC_ratio and 0.76 when using ADC_tumour value when discriminating Gleason 6 from Gleason ≥7 tumours. Inter-observer reliability in the calculation of ADC ratios was excellent, with ICC of 0.964.

Conclusion

ADC_ratio is a reliable and reproducible tool in quantification of diffusion restriction for clinically significant prostate cancer foci.

An imaging-based approach predicts clinical outcomes in prostate cancer through a novel support vector machine classification

Preoperatively predict the probability of Prostate cancer (PCa) biochemical recurrence (BCR) is of definite clinical relevance. The purpose of this study was to develop an imaging-based approach in the prediction of 3-years BCR through a novel support vector machine (SVM) classification. We collected clinicopathologic and MR imaging datasets in 205 patients pathologically confirmed PCa after radical prostatectomy. Univariable and multivariable analyses were used to assess the association between MR findings and 3-years BCR, and modeled the imaging variables and follow-up data to predict 3-year PCa BCR using SVM analysis. The performance of SVM was compared with conventional Logistic regression (LR) and D'Amico risk stratification scheme by area under the receiver operating characteristic curve (Az) analysis. We found that SVM had significantly higher Az (0.959 vs. 0.886; p = 0.007), sensitivity (93.3% vs. 83.3%; p = 0.025), specificity (91.7% vs. 77.2%; p = 0.009) and accuracy (92.2% vs. 79.0%; p = 0.006) than LR analysis. Performance of popularized D'Amico scheme was effectively improved by adding MRI-derived variables (Az: 0.970 vs. 0.859, p < 0.001; sensitivity: 91.7% vs. 86.7%, p = 0.031; specificity: 94.5% vs. 78.6%, p = 0.001; and accuracy: 93.7% vs. 81.0%, p = 0.007). Additionally, beside pathological Gleason score (hazard ratio [HR] = 1.560, p = 0.008), surgical-T3b (HR = 4.525, p < 0.001) and positive surgical margin (HR = 1.314, p = 0.007), apparent diffusion coefficient (HR = 0.149, p = 0.035) was the only independent imaging predictor of time to PSA failure. Therefore, We concluded that imaging-based approach using SVM was superior to LR analysis in predicting PCa outcome. Adding MR variables improved the performance of D'Amico scheme.

Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings

Early identification of PCa patients at risk for biochemical recurrence (BCR) post-therapy will potentially complement definitive therapy with either neo- or adjuvant therapy to improve prognosis. BCR post definitive therapy is often associated with disease progression that might cause a bulge in the prostate gland. In this work we explored if an atlas-based comparison approach reveals shape differences in the prostate capsule as observed on pre-treatment T2-weighted MRI between prostate cancer patients who do (BCR⁺) and do not (BCR⁻) have BCR following definitive therapy. A single center IRB approved study included 874 patients. Complete image datasets, clinically localized PCa, availability of Gleason score, data available for post-treatment PSA and follow-up for at least 3 years in patients without BCR were the inclusion criteria to select 77 patients out of the 874 patients. Further controlling for Gleason score, stage, age and to maintain equal number of cases for the BCR⁺ and BCR⁻ categories, the total number of cases was reduced to 50. Manually segmented prostate capsules were aligned to a BCR⁻ template for statistical comparison between the BCR⁺ and BCR⁻ groups. Statistically significant shape difference between the two groups was observed towards the lateral and the posterior sides of prostate.

Pathological and 3 Tesla Volumetric Magnetic Resonance Imaging Predictors of Biochemical Recurrence after Robotic Assisted Radical Prostatectomy: Correlation with Whole Mount Histopathology

PURPOSE

We sought to identify the clinical and magnetic resonance imaging variables predictive of biochemical recurrence after robotic assisted radical prostatectomy in patients who underwent multiparametric 3 Tesla prostate magnetic resonance imaging.

MATERIALS AND METHODS

We performed an institutional review board approved, HIPAA (Health Insurance Portability and Accountability Act) compliant, single arm observational study of 3 Tesla multiparametric magnetic resonance imaging prior to robotic assisted radical prostatectomy from December 2009 to March 2016. Clinical, magnetic resonance imaging and pathological information, and clinical outcomes were compiled. Biochemical recurrence was defined as prostate specific antigen 0.2 ng/cc or greater. Univariate and multivariate regression analysis was performed.

RESULTS

Biochemical recurrence had developed in 62 of the 255 men (24.3%) included in the study at a median followup of 23.5 months. Compared to the subcohort without biochemical recurrence the subcohort with biochemical recurrence had a greater proportion of patients with a high grade biopsy Gleason score, higher preoperative prostate specific antigen (7.4 vs 5.6 ng/ml), intermediate and high D'Amico classifications, larger tumor volume on magnetic resonance imaging (0.66 vs 0.30 ml), higher PI-RADS® (Prostate Imaging-Reporting and Data System) version 2 category lesions, a greater proportion of intermediate and high grade radical prostatectomy Gleason score lesions, higher pathological T3 stage (all p <0.01) and a higher positive surgical margin rate (19.3% vs 7.8%, p = 0.016). On multivariable analysis only tumor volume on magnetic resonance imaging (adjusted OR 1.57, p = 0.016), pathological T stage (adjusted OR 2.26, p = 0.02), positive surgical margin (adjusted OR 5.0, p = 0.004) and radical prostatectomy Gleason score (adjusted OR 2.29, p = 0.004) predicted biochemical recurrence.

CONCLUSIONS

In this cohort tumor volume on magnetic resonance imaging and pathological variables, including Gleason score, staging and positive surgical margins, significantly predicted biochemical recurrence. This suggests an important new imaging biomarker.

The Role of PET/MR Imaging in Precision Medicine

Fluorodeoxyglucose PET and PET/computed tomography have gained acceptance in the evaluation of disease. Nontargeted tracers have been used in the diagnosis of certain malignancies but may not be sensitive or specific enough to become standard of care. Newer targeted PET tracers have been developed that target disease-specific biomarkers, and allow accurate and sensitive detection of disease. Combined with the capabilities of MR imaging to evaluate soft tissue, precision imaging with PET/MR imaging can change the diagnosis. This article discusses specific areas in which precision imaging with nontargeted and targeted diagnostic agents can change the diagnosis and treatment.

Role of MRI in the Risk Assessment of Primary Prostate Cancer

A successful paradigm shift toward personalized management strategies for patients with prostate cancer (PCa) is heavily dependent on the availability of noninvasive diagnostic tools capable of accurately establishing the true extent of disease at the time of diagnosis and estimating the risk of subsequent disease progression and related mortality. Although there is still considerable scope for improvement in its diagnostic, predictive, and prognostic capabilities, multiparametric prostate magnetic resonance imaging (MRI) is currently regarded as the imaging modality of choice for local staging of PCa. A negative MRI, that is, the absence of any MRI-visible intraprostatic lesion, has a high negative predictive value for the presence of clinically significant PCa and can substantiate the consideration of active surveillance as a preferred initial management approach. MRI-derived quantitative and semi-quantitative parameters can be utilized to noninvasively characterize MRI-visible prostate lesions and identify those patients who are most likely to benefit from radical treatment, and differentiate them from patients with benign or indolent prostate pathology that may also be visible on MRI. This literature review summarizes current strategies how MRI can be used to determine a tailored management strategy for an individual patient.

Relationship between Gleason score and apparent diffusion coefficients of diffusion-weighted magnetic resonance imaging in prostate cancer patients

INTRODUCTION

We assessed the correlation between the apparent diffusion coefficient (ADC) and pathological Gleason score (GS) of prostate cancer patients.

METHODS

A total of 125 patients who underwent multiparametric magnetic resonance imaging before radical prostatectomy for prostate cancer were included in this study. ADC values were compared with different GS. We used receiver operating characteristic analysis and determined the ADC cutoff value to differentiate tumours with a GS of 6 from those with a GS ≥7.

RESULTS

We identified 34 patients (27.2%) with a GS of 6; 33 patients (26.4%) with a GS of 7; 22 patients (17.6%) with a GS of 8; and 36 patients (28.8%) with a GS of ≥9. The mean ADC value for disease with a GS of 6 was 0.914 ± 0.161 ×10^-3 mm²/s; GS of 7: 0.741 ± 0.164 ×10^-3 mm²/s; GS of 8: 0.679 ± 0.130 ×10^-3 mm²/s; and GS of ≥9: 0.593 ± 0.089 ×10^-3 mm²/s. An ADC value of 0.830 ×10^-3mm²/s was the best cutoff value to identify prostate cancer with a GS of 6.

CONCLUSIONS

We observed an inverse relationship between GS and ADC value. Moreover, a cutoff ADC value may help differentiate disease with a GS of 6 from disease with a GS ≥7.

Correlation between apparent diffusion coefficient value on diffusion-weighted MR imaging and Gleason score in prostate cancer

OBJECTIVES

To investigate whether diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) correlates with prostate cancer aggressiveness and further to compare the diagnostic performance of ADC and normalized ADC (nADC: normalized to non-tumor tissue).

PATIENTS AND METHODS

Thirty pre-treatment patients (mean age, 69years; range: 59-78years) with prostate cancer underwent magnetic resonance imaging (MRI) examination, including DWI with three b values: 50, 400, and 800s/mm². Both ADC and nADC were correlated with the Gleason score obtained through transrectal ultrasound-guided biopsy.

RESULTS

The tumor minimum ADC (ADC_min: the lowest ADC value within tumor) had an inverse correlation with the Gleason score (r=-0.43, P<0.05), and it was lower in patients with Gleason score 3+4 than in those with Gleason score 3+3 (0.54±0.11×10³mm²/s vs. 0.64±0.12×10^-3mm²/s, P<0.05). Both the nADC_min and nADC_mean correlated with the Gleason score (r=-0.52 and r=-0.55, P<0.01; respectively), and they were lower in patients with Gleason score 3+4 than those with Gleason score 3+3 (P<0.01; respectively). Receiver operating characteristic (ROC) analysis showed that the area under the ROC curve was 0.765, 0.818, or 0.833 for the ADC_min, nADC_min, or nADC_mean; respectively, in differentiating between Gleason score 3+4 and 3+3 tumors.

CONCLUSION

Tumor ADC_min, nADC_min, and nADC_mean are useful markers to predict the aggressiveness of prostate cancer.

Risk stratification of prostate cancer: integrating multiparametric MRI, nomograms and biomarkers

Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.

The expanding landscape of diffusion-weighted MRI in prostate cancer

The added value of diffusion-weighted magnetic resonance imaging (DW-MRI) for the detection, localization, and staging of primary prostate cancer has been extensively reported in original studies and meta-analyses. More recently, DW-MRI and related techniques have been used to noninvasively assess prostate cancer aggressiveness and estimate its biological behavior. The present article aims to summarize the potential applications of DW-MRI for noninvasive optimization of pretherapeutic risk assessment, patient management decisions, and evaluation of treatment response.

Prostate Cancer: Utility of Whole-Lesion Apparent Diffusion Coefficient Metrics for Prediction of Biochemical Recurrence After Radical Prostatectomy

OBJECTIVE

The purpose of this study was to investigate the additional value of whole-lesion histogram apparent diffusion coefficient (ADC) metrics, when combined with standard pathologic features, in prediction of biochemical recurrence (BCR) after radical prostatectomy for prostate cancer.

MATERIALS AND METHODS

The study included 193 patients (mean age, 61 ± 7 years) who underwent 3-T MRI with DWI (b values, 50 and 1000 s/mm(2)) before prostatectomy. Histogram metrics were derived from 3D volumes of interest encompassing the entire lesion on ADC maps. Pathologic features from radical prostatectomy and subsequent BCR were recorded for each patient. The Fisher exact test and Mann-Whitney test were used to compare ADC-based metrics and pathologic features between patients with and patients without BCR. Stepwise logistic regression analysis was used to construct multivariable models for prediction of BCR, which were assessed by ROC analysis.

RESULTS

BCR occurred in 16.6% (32/193) of patients. Variables significantly associated with BCR included primary Gleason grade, Gleason score, extraprostatic extension, seminal vesicle invasion, positive surgical margin, preoperative prostate-specific antigen level, MRI tumor volume, mean whole-lesion ADC, entropy ADC, and mean ADC of the bottom 10th, 10-25th, and 25-50th percentiles (p ≤ 0.019). Significant independent predictors of BCR at multivariable analysis were primary Gleason grade, extraprostatic extension, mean of the bottom 10th percentile ADC, and entropy ADC (p = 0.002-0.037). The AUC of this multivariable model was 0.94 for prediction of BCR; the AUC of pathologic features alone was 0.89 (p = 0.001).

CONCLUSION

A model integrating whole-lesion ADC metrics had significantly higher performance for prediction of BCR than did standard pathologic features alone and may help guide postoperative prognostic assessments and decisions regarding adjuvant therapy.

Prediction of biochemical recurrence after radical prostatectomy with PI-RADS version 2 in prostate cancers: initial results

OBJECTIVES

To determine whether the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) helps predict biochemical recurrence (BCR) after radical prostatectomy for prostate cancer (PCa).

METHODS

We included 158 patients with PCa who underwent magnetic resonance imaging (MRI) and radical prostatectomy (RP). Clinical (prostate-specific antigen, greatest percentage of core, and percentage of positive core number), PI-RADSv2 score on MRI, and surgical parameters (Gleason score, extracapsular extension, seminal vesicle invasion, and tumour volume) were investigated. Univariate and multivariate analyses using Cox's proportional hazards model were performed to assess parameters predictive of BCR (two consecutive prostate specific antigens ≥0.2 ng/ml). Kaplan-Meier survival curves were analyzed.

RESULTS

The rate of BCR was 13.3 % (21/158) after surgery (median follow-up, 25 months; range, 12-36). No subject with a PI-RADS score <4 had BCR. In univariate analysis, all parameters were significant for BCR (p < 0.05), except seminal vesicle invasion (p = 0.254). Meanwhile, PI-RADS score was the only independent parameter for BCR in multivariate analysis (p < 0.05). Two-year, BCR-free survival post-RP was significantly lower for PI-RADS ≥4 (84.7-85.5 %) than for PI-RADS <4 (100 %; p < 0.05).

CONCLUSION

As a preoperative imaging tool, PI-RADSv2 may be useful to predict BCR after radical prostatectomy for PCa.

KEY POINTS

• No subject with PI-RADS <4 had BCR after RP • PI-RADSv2 was the only predictor of BCR in multivariate analysis • Two-year, BCR-free survival following RP was lower for PI-RADS≥4 than for PI-RADS<4 • Inter-rater agreement was good for PI-RADS ≥4 or not.

Apparent diffusion coefficient: An associative factor for recurrence after nephrectomy in localized renal cell carcinoma

PURPOSE

To investigate whether the apparent diffusion coefficient (ADC) of a tumor is associated with recurrence after nephrectomy in renal cell carcinoma (RCC) MATERIALS AND METHODS: We retrospectively studied 49 patients with localized RCC who underwent 1.5T magnetic resonance imaging (MRI) including diffusion-weighted imaging preoperatively. Fifteen patients had recurrent disease after surgery. The ADC was measured by placing a region-of-interest in a solid region of each tumor on the ADC map. We named the average value of the three ADC values the "average ADC" and the lowest ADC value among the three as the "minimum ADC." The correlations between clinicopathological factors including patient age and gender, tumor side, tumor size, growth/invasion pattern, Fuhrman grade, histological subtype, venous invasion, average and minimum ADCs, and disease-free survival were analyzed by Cox proportional hazards model.

RESULTS

In univariate analysis, tumor size, venous invasion, mean ADC, and minimum ADC showed significant correlations with disease-free survival (P < 0.05). In multivariate analysis, only venous invasion and minimum ADC were significant (P < 0.05). The 5-year disease-free survival rate of the low minimum ADC group was 51.6%, while that of the high minimum ADC group was 85.1%.

CONCLUSION

The minimum ADC of a tumor, although not as pronounced as venous invasion, was found to be an independent associative factor for recurrence after nephrectomy in patients with localized RCC.

Interpretation and reporting multiparametric prostate MRI: a primer for residents and novices

Multiparametric MRI has developed as a tool for prostate cancer lesion detection, characterization, staging, surveillance, and imaging of local recurrence. Given the disease frequency and the growing importance of imaging, as reliance on PSA declines, radiologists involved in prostate MRI imaging must become proficient with the fundamentals of multiparametric prostate MRI (T2WI, DWI, DCE-MRI, and MR spectroscopy). Interpretation and reporting must yield accuracy, consistency, and add value to clinical care. This review provides a primer to novices and trainees learning about multiparametric prostate MRI. MRI technique is presented along with the use of particular MRI sequences. Relevant prostate anatomy is outlined and imaging features of prostate cancer with staging are discussed. Finally structured reporting is introduced, and some limitations of prostate MRI are discussed.

Functional MRI and CT biomarkers in oncology

Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T1 relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R2*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives.

Diffusion-weighted imaging to evaluate for changes from androgen deprivation therapy in prostate cancer

OBJECTIVE

The objective of our study was to investigate the usefulness of apparent diffusion coefficient (ADC) values in evaluating for therapeutic changes from androgen deprivation therapy (ADT) in prostate cancer patients.

MATERIALS AND METHODS

Forty-eight patients with prostate cancer treated with ADT were enrolled in this retrospective study. Diffusion-weighted imaging (DWI) at 3 T was performed before and after ADT. Before and after treatment, ADC values were measured in the tumors and in the benign tissues of the prostate, and serum prostate-specific antigen (PSA) levels and prostate volumes were also assessed. Statistical analysis was performed using a paired Student t test, Wilcoxon signed rank test, and Spearman rank correlation.

RESULTS

In 48 patients, 55 tumors were identified. After treatment, the mean ADC value of the tumors (1.06×10(-3) mm2/s) was significantly increased as compared with the pretreatment value (0.78×10(-3) mm2/s) (p<0.001), whereas the ADC values of the benign tissues after treatment were significantly decreased compared with the pretreatment values (p<0.001). The mean prostate volume and mean PSA level were significantly reduced from 42.8 cm3 and 153.60 ng/mL before treatment to 21.4 cm3 and 9.51 ng/mL, respectively, after treatment (p<0.001). Changes in tumor ADC values showed a weak negative correlation with changes in PSA levels after treatment (correlation coefficient, ρ=-0.320; p=0.028).

CONCLUSION

DWI may have potential as a noninvasive tool for monitoring changes in response to ADT in prostate cancer patients.

Diffusion-weighted magnetic resonance imaging for prediction of insignificant prostate cancer in potential candidates for active surveillance

OBJECTIVES

To investigate whether the apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (DW-MRI) could help improve the prediction of insignificant prostate cancer in candidates for active surveillance (AS).

METHODS

Enrolled in this retrospective study were 287 AS candidates who underwent DW-MRI before radical prostatectomy. Patients were stratified into two groups; Group A consisted of patients with no visible tumour or a suspected tumour ADC value > 0.830 × 10(-3) mm(2)/sec and Group B consisted of patients with a suspected tumour ADC value < 0.830 × 10(-3) mm(2)/sec. We compared pathological outcomes in each group.

RESULTS

Group A had 243 (84.7 %) patients and Group B had 44 (15.3 %) patients. The proportion of organ-confined Gleason ≤ 6 disease and insignificant prostate cancer was significantly higher in Group A than Group B (61.3 % vs. 38.6 %, p = 0.005 and 47.7 % vs. 25.0 %, p = 0.005, respectively). On multivariate analysis, a high ADC value was the independent predictor of organ-confined Gleason ≤ 6 disease and insignificant prostate cancer (odds ratio = 2.43, p = 0.011 and odds ratio = 2.74, p = 0.009, respectively).

CONCLUSION

Tumour ADC values may be a useful marker for predicting insignificant prostate cancer in candidates for AS.

KEY POINTS

• ADC from DW-MRI can help assess prostate cancer aggressiveness in potential AS candidates. • There was a closed correlation between higher ADC values and insignificant prostate cancer. • The absence of lesions on DWI/DWI can help select potential AS candidates.

Diffusion-weighted imaging of the male pelvis

Diffusion-weighted (DW) imaging is playing an increasingly important role in disease detection, prognostication, and monitoring of treatment response. Particularly in the realm of oncology, the potential applications for DW imaging continue to expand. In this article, the authors detail the role of DW imaging for pathologic processes involving the male pelvis. The authors describe the current data, new insights, and ongoing controversies regarding DW imaging of the male pelvis with a particular emphasis on oncologic applications. The authors also discuss imaging techniques and common pitfalls for DW imaging in this anatomic region.

Preoperative 3-T diffusion-weighted MRI for the qualitative and quantitative assessment of extracapsular extension in patients with intermediate- or high-risk prostate cancer

OBJECTIVE

The purpose of this study was to prospectively evaluate the value of diffusion-weighted MRI (DWI) for the assessment of extracapsular extension (ECE) in patients with prostate cancer.

SUBJECTS AND METHODS

Between November 2010 and April 2012, 40 patients with intermediate- to high-risk prostate cancer were prospectively recruited. MR images were obtained at 3 T with a phased-array coil. Two independent readers scored the T2-weighted images alone and then in combination with DW images. ROIs were drawn on the apparent diffusion coefficient (ADC) maps, and histogram-derived values were calculated. Whole-mount histopathologic examination was the standard of reference. Reader performance was analyzed, and differences in patient characteristics and histogram-based ADC values, according to ECE status, were evaluated.

RESULTS

ECE was present in 23 of 40 (58%) patients and 23 of 43 (53%) tumors. The sensitivity for side-specific ECE detection significantly increased, from 0.22 to 0.44 for reader 1 and 0.33 to 0.82 for reader 2 (both p < 0.05) without a significant change in specificity for either reader with the addition of DWI and ADC mapping. The positive and negative predictive values for both readers also increased. The ADC parameters of median and 10th and 25th centiles showed a statistically significant difference between tumors with and those without ECE (p < 0.05).

CONCLUSION

The addition of DWI and ADC mapping to T2-weighted MRI improved the accuracy of preoperative detection of ECE. Median and 10th and 25th centile ADC values were significantly associated with the presence of ECE and may be useful in the pretreatment assessment of patients with prostate cancer.

High-resolution diffusion-weighted imaging of the prostate

OBJECTIVE

The purpose of this study was to evaluate the effect of increasing the spatial resolution of the prostate DWI protocol on image quality and lesion conspicuity.

SUBJECTS AND METHODS

Twenty-nine patients with biopsy-proven prostate cancer undergoing MRI examinations were imaged with two diffusion-weighted imaging (DWI) protocols: current standard clinical protocol (6.7 mm(3) voxels) and a new high-resolution protocol (3.1 mm(3) voxels). Diffusion-weighted images were independently and subjectively scored on lesion conspicuity, internal architecture definition, and overall image quality by two radiologists. Average apparent diffusion coefficient (ADC) values were measured in normal tissue and cancerous lesions on both sequences. Reader scores and ADC and contrast values were compared between the two protocols. Cancer ADC values were correlated with Gleason scores.

RESULTS

The signal-to-noise ratio of the new high-resolution DWI protocol was 40% lower than that of the standard protocol. The reader scores were higher by 0.73 (range, 0.29-1.16) grades, or 19% (range, 7-32%), on average, for the new protocol, indicating better image quality. The average ADC values were 8% higher with the new protocol, with ADC contrast values between cancer and normal prostate unchanged. There was marginally significant correlation of cancer ADC values with Gleason scores (p = 0.05, r ≈ -0.36).

CONCLUSION

We showed that for DWI of the prostate at 3-7 mm(3) voxel sizes the benefits of higher spatial resolution outweigh the effects of reduced signal-to-noise and contrast-to-noise ratios, potentially improving the sensitivity to small or sparse prostate cancers. Radiologists can consider using higher-spatial-resolution DWI sequences in their practices.

Prostate cancer: role of pretreatment multiparametric 3-T MRI in predicting biochemical recurrence after radical prostatectomy

OBJECTIVE

The purpose of this study is to retrospectively investigate whether pretreatment multiparametric MRI findings can predict biochemical recurrence in patients who underwent radical prostatectomy (RP) for localized prostate cancer.

MATERIALS AND METHODS

In this study, 282 patients with biopsy-proven prostate cancer who received RP underwent pretreatment MRI using a phased-array coil at 3 T, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI (DCE-MRI). MRI variables included apparent tumor presence on combined imaging sequences, extracapsular extension, and tumor size on DWI or DCE-MRI. Clinical variables included baseline prostate-specific antigen (PSA) level, clinical stage, and Gleason score at biopsy. The relationship between clinical and imaging variables and biochemical recurrence was evaluated using Cox regression analysis.

RESULTS

After a median follow-up of 26 months, biochemical recurrence developed in 61 patients (22%). Univariate analysis revealed that all the imaging and clinical variables were significantly associated with biochemical recurrence (p < 0.01). On multivariate analysis, however, baseline PSA level (p = 0.002), Gleason score at biopsy (p = 0.024), and apparent tumor presence on combined T2WI, DWI, and DCE-MRI (p = 0.047) were the only significant independent predictors of biochemical recurrence. Of the independent predictors, apparent tumor presence on combined T2WI, DWI, and DCE-MRI showed the highest hazard ratio (2.38) compared with baseline PSA level (hazard ratio, 1.05) and Gleason score at biopsy (hazard ratio, 1.34).

CONCLUSION

The apparent tumor presence on combined T2WI, DWI, and DCE-MRI of pretreatment MRI is an independent predictor of biochemical recurrence after RP. This finding may be used to construct a predictive model for biochemical recurrence after surgery.

Role of multiparametric 3.0-Tesla magnetic resonance imaging in patients with prostate cancer eligible for active surveillance

OBJECTIVE

To evaluate predictors of more aggressive disease and the role of multiparametric 3.0-T magnetic resonance imaging (MRI) in selecting patients with prostate cancer for active surveillance (AS).

PATIENTS AND METHODS

We retrospectively assessed 298 patients with prostate cancer who met the Prostate Cancer Research International: Active Surveillance (PRIAS) criteria, defined as T1c/T2, PSA level of ≤10 ng/mL, PSA density (PSAD) of <0.2 ng/mL(2) , Gleason score <7, and one or two positive biopsy cores. All patients underwent preoperative MRI, including T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging, as well as radical prostatectomy (RP) between June 2005 and December 2011. Imaging results were correlated with pathological findings to evaluate the ability of MRI to select patients for AS.

RESULTS

In 35 (11.7%) patients, no discrete cancer was visible on MRI, while in the remaining 263 (88.3%) patients, a discrete cancer was visible. Pathological examination of RP specimens resulted in upstaging (>T2) in 21 (7%) patients, upgrading (Gleason score >6) in 136 (45.6%), and a diagnosis of unfavourable disease in 142 (47.7%) patients. The 263 patients (88.3%) with visible cancer on imaging were more likely to have their cancer status upgraded (49.8% vs 14.3%) and be diagnosed with unfavourable disease (52.1% vs 14.3%) than the 35 patients (11.7%) with no cancer visible upon imaging, and these differences were statistically significant (P < 0.001 for all). A visible cancer lesion on MRI, PSAD, and patient age were found to be predictors of unfavourable disease in multivariate analysis.

CONCLUSION

MRI can predict adverse pathological features and be used to assess the eligibility of patients with prostate cancer for AS.

Incorporating prognostic imaging biomarkers into clinical practice

A prognostic imaging biomarker can be defined as an imaging characteristic that is objectively measurable and provides information on the likely outcome of the cancer disease in an untreated individual and should be distinguished from predictive imaging biomarkers and imaging markers of response. A range of tumour characteristics of potential prognostic value can be measured using a variety imaging modalities. However, none has currently been adopted into routine clinical practice. This article considers key examples of emerging prognostic imaging biomarkers and proposes an evaluation framework that aims to demonstrate clinical efficacy and so support their introduction into the clinical arena. With appropriate validation within an established evaluation framework, prognostic imaging biomarkers have the potential to contribute to individualized cancer care, in some cases reducing the financial burden of expensive cancer treatments by facilitating their more rational use.