The association of tumor volume with mortality following radical prostatectomy

Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma

BACKGROUND

 Imaging biomarkers are quantitative parameters from imaging modalities, which are collected noninvasively, allow conclusions about physiological and pathophysiological processes, and may consist of single (monoparametric) or multiple parameters (bi- or multiparametric).

METHOD

 This review aims to present the state of the art for the quantification of multimodal and multiparametric imaging biomarkers. Here, the use of biomarkers using artificial intelligence will be addressed and the clinical application of imaging biomarkers in breast and prostate cancers will be explained. For the preparation of the review article, an extensive literature search was performed based on Pubmed, Web of Science and Google Scholar. The results were evaluated and discussed for consistency and generality.

RESULTS AND CONCLUSION

 Different imaging biomarkers (multiparametric) are quantified based on the use of complementary imaging modalities (multimodal) from radiology, nuclear medicine, or hybrid imaging. From these techniques, parameters are determined at the morphological (e. g., size), functional (e. g., vascularization or diffusion), metabolic (e. g., glucose metabolism), or molecular (e. g., expression of prostate specific membrane antigen, PSMA) level. The integration and weighting of imaging biomarkers are increasingly being performed with artificial intelligence, using machine learning algorithms. In this way, the clinical application of imaging biomarkers is increasing, as illustrated by the diagnosis of breast and prostate cancers.

KEY POINTS

· Imaging biomarkers are quantitative parameters to detect physiological and pathophysiological processes.. · Imaging biomarkers from multimodality and multiparametric imaging are integrated using artificial intelligence algorithms.. · Quantitative imaging parameters are a fundamental component of diagnostics for all tumor entities, such as for mammary and prostate carcinomas..

CITATION FORMAT

· Bäuerle T, Dietzel M, Pinker K et al. Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Fortschr Röntgenstr 2024; 196: 354 - 362.

How reliable is the high-volume definition in prostate cancer patients: the potential game-changing role of PSMA

PURPOSE

To evaluate whether metabolic and volumetric data from 68 Ga-PSMA PET/CT performed during staging of de-novo high-volume mCSPC patients who received docetaxel could be used to predict survival.

METHODS

Forty-two de-novo high-volume mCSPC patients, who received ADT + Docetaxel and underwent 68 Ga-PSMA PET/CT for staging, were included in the study. The association between patients' pathological data, all PSA measurements, treatments they received, the data obtained from 68 Ga-PSMA PET/CT and progression-free and overall survival were examined.

RESULTS

In the multivariate analysis, PSMA-TV (primary) and PSMA-TV (WB) variables were shown to be independent negative predictors of overall survival. For the threshold value of 19.91 cm 3 obtained for PSMA-TV (primary), HR was calculated as 6.31, the 95% confidence interval (CI): 1.01-39.18, P = 0.048. For the threshold value of 1226.5 cm 3 obtained for PSMA-TV (WB) variable, HR was calculated as 58.62, the 95% CI: 2.55-1344.43, P = 0.011. In our study, SUVmax (WB) variable was found to be an independent and negative predictor of progression-free survival. For the determined threshold value of 17.74, HR was calculated as 16.24, 95% CI: 1.18-22.76, P = 0.037.

CONCLUSION

Metabolic and volumetric data obtained from 68 Ga-PSMA PET/CT can be used to predict survival in de-novo high-volume mCSPC. Our results show that in ADT + Docetaxel receiving patients, a subgroup with higher PSMA-TV (WB) values have a significantly worse prognosis. This situation suggests that the high-volume disease definition in the literature may be insufficient for this group, and that 68 Ga-PSMA PET/CT can play an essential role in demonstrating the heterogeneity within the group.

The role of tumor density in predicting significant cancer on targeted biopsy of the prostate

OBJECTIVE

Multiparametric magnetic resonance imaging (mpMRI) is central to diagnosing prostate cancer; however, not all imaged lesions represent clinically significant tumors. We aimed to evaluate the association between the relative tumor volume on mpMRI and clinically significant prostate cancer on biopsy.

MATERIALS AND METHODS

We retrospectively reviewed the medical records of 340 patients who underwent combined transperineal targeted and systematic prostate biopsies between 2017 and 2021. Tumor volume was estimated based on the mpMRI diameter of suspected lesions. Relative tumor volume (tumor density) was calculated by dividing the tumor and prostate volumes. The study outcome was clinically significant cancer on biopsy. Logistic regression analyses were used to evaluate the association between tumor density and the outcome. The cutoff for tumor density was determined with ROC curves.

RESULTS

Median estimated prostate and peripheral zone tumor volumes were 55cm3 and 0.61cm3, respectively. Median PSA density was 0.13 and peripheral zone tumor density was 0.01. Overall, 231 patients (68%) had any cancer and 130 (38%) had clinically significant cancer. On multivariable logistic regression age, PSA, previous biopsy, maximal PI-RADS score, prostate volume, and peripheral zone tumor density were significant predictors of outcome. Using a threshold of 0.006, the sensitivity, specificity, positive and negative predictive values of peripheral zone tumor density were 0.9, 0.51, 0.57, and 0.88, respectively.

CONCLUSION

Peripheral zone tumor density is associated with clinically significant prostate cancer in patients with PI-RADS 4 and 5 mpMRI lesions. Future studies are required to validate our findings and evaluate the role of tumor density in avoiding unnecessary biopsies.

MRI-derived tumor volume as a predictor of biochemical recurrence and adverse pathology in patients after radical prostatectomy: a propensity score matching study

PURPOSE

To investigate the predictive value of MRI-derived tumor volume (TV) of biochemical recurrence (BCR) and adverse pathology (AP) in patients following radical prostatectomy (RP).

METHODS

The data of 565 patients receiving RP in a single institution between 2010 and 2021 were retrospectively analyzed. All suspicious tumor foci were delineated manually using ITK-SNAP software as the regions of interest (ROIs). The sum of the TV of all lesions was calculated automatically based on the voxel in the ROIs to acquire the final TV parameter. TV was categorized as low-volume (≤ 6.5 cm³) and high-volume (> 6.5 cm³) based on the cut-off value. Univariate and multivariate Cox and logistic regression analyses were performed to identify independent predictors of BCR and AP. The Kaplan-Meier with the log-rank test was conducted to compare the BCR-free survival (BFS) between the low and high-volume groups.

RESULTS

All the included patients were divided into the low-volume group (n = 337) and the high-volume group (n = 228). The TV was an independent predictor of BFS in the multivariate Cox regression analysis (Hazard Ratio (HR) [95% CI]: 1.550 [1.066-2.256], P = 0.022). The Kaplan-Meier analysis demonstrated that low volume was associated with a better BFS than high volume before propensity score matching (PSM) (P < 0.001). One hundred and fifty-eight pairs were obtained by 1:1 PSM to balance the baseline parameters between the two groups. After the PSM, low-volume remained to be associated with a better BFS than high-volume (P = 0.006). TV as a categorical variable was an independent factor of AP in multivariate logistic regression analysis (Odd ratio (OR) [95% CI]: 1.821 [1.064-3.115], P = 0.029). After balancing the potential factors influencing AP by 1:1 PSM, 162 new pairs were identified. The high-volume group had a higher AP rate than the low-volume group after PSM (75.9 vs. 64.8%, P = 0.029).

CONCLUSION

We adopted a novel approach to acquiring the TV on preoperative MRI. TV was significantly associated with BFS and AP of patients undergoing RP, which was further illustrated by PSM analysis. MRI-derived TV may serve as a predictive marker for assessing BFS and AP in further studies, which will facilitate clinical decision-making and patient counseling.

Using PSMA imaging for prognostication in localized and advanced prostate cancer

The use of prostate-specific membrane antigen (PSMA)-directed applications in modern prostate cancer management has evolved rapidly over the past few years, helping to establish new treatment pathways and provide further insights into prostate cancer biology. However, the prognostic implications of PSMA-PET have not been studied systematically, owing to rapid clinical implementation without long follow-up periods to determine intermediate-term and long-term oncological outcomes. Currently available data suggest that traditional prognostic factors and survival outcomes are associated with high PSMA expression (both according to immunohistochemistry and PET uptake) in men with localized and biochemically recurrent disease. Treatment with curative intent (primary and/or salvage) often fails when PSMA-positive metastases are present; however, the sensitivity of PSMA-PET in detecting all metastases is poor. Low PSMA-PET uptake in recurrent disease is a favourable prognostic factor; however, it can be associated with poor prognosis in conjunction with high ¹⁸F-fluorodeoxyglucose uptake in metastatic castration-resistant prostate cancer. Clinical trials embedding PSMA-PET for guiding management with reliable oncological outcomes are needed to support ongoing clinical use.

The Quantitative Assessment of Using Multiparametric MRI for Prediction of Extraprostatic Extension in Patients Undergoing Radical Prostatectomy: A Systematic Review and Meta-Analysis

Purpose

To investigate the diagnostic performance of using quantitative assessment with multiparametric MRI (mpMRI) for prediction of extraprostatic extension (EPE) in patients with prostate cancer (PCa).

Methods

We performed a computerized search of MEDLINE, Embase, Cochrane Library, Web of Science, and Google Scholar from inception until July 31, 2021. Summary estimates of sensitivity and specificity were pooled with the bivariate model, and quality assessment of included studies was performed with the Quality Assessment of Diagnostic Accuracy Studies-2. We plotted forest plots to graphically present the results. Multiple subgroup analyses and meta-regression were performed to explore the variate clinical settings and heterogeneity.

Results

A total of 23 studies with 3,931 participants were included. The pooled sensitivity and specificity for length of capsular contact (LCC) were 0.79 (95% CI 0.75-0.83) and 0.77 (95% CI 0.73-0.80), for apparent diffusion coefficient (ADC) were 0.71 (95% CI 0.50-0.86) and 0.71 (95% CI 059-0.81), for tumor size were 0.62 (95% CI 0.57-0.67) and 0.75 (95% CI 0.67-0.82), and for tumor volume were 0.77 (95% CI 0.68-0.84) and 0.72 (95% CI 0.56-0.83), respectively. Substantial heterogeneity was presented among included studies, and meta-regression showed that publication year (≤2017 vs. >2017) was the significant factor in studies using LCC as the quantitative assessment (P=0.02).

Conclusion

Four quantitative assessments of LCC, ADC, tumor size, and tumor volume showed moderate to high diagnostic performance of predicting EPE. However, the optimal cutoff threshold varied widely among studies and needs further investigation to establish.

Cribriform glands are associated with worse outcome than other pattern 4 subtypes: A study of prognostic and clinicopathological characteristics of prostate adenocarcinoma with an emphasis on Grade Groups

AIM

Although prostate adenocarcinoma is the most common cancer in men, survival is quite high and with the help of histopathological examination using the updated classification, patient management strategies are developing. We aimed to evaluate the correlation between the histopathological features and biochemical recurrence (BCR) in patients who underwent radical prostatectomy (RP) using the new classification.

METHODS

A total of 285 prostate adenocarcinoma cases that underwent RP between January 2009 and December 2017 and followed up for at least 3 months were included in the study. The cases were re-evaluated according to WHO-ISUP 2016 classification and the findings were recorded.

RESULTS

The mean age was 63,4 years. Gleason scores of the cases were as follows: 3+3 144 cases (50.5%), 3+4 81 cases (28.4%), 4+3 28 cases (9.8%), 4+4 7 cases (2.5%) , 3+5 6 cases (2.1%), 5+3 2 cases (0.7%), 4+5 17 cases (6%). There were 198 (69,5%) pT2, 54 (18,9%) pT3a and 33 (11,6%) pT3b cases. The mean follow-up time was 44,1 months and BCR was detected in 97 cases (34%). The relationship between the Group Grades and BCR was statistically significant. BCR rate increased as the tumour volume and the percentage of pattern 4 increased (P < .001).There was a significant correlation between preoperative PSA value, extraprostatic extension, seminal vesicle invasion, surgical margin positivity, tumour volume, pattern 4 percentage, presence of cribriform glands and BCR and recurrence-free survival in both univariate and multivariate analysis and recurrence-free survival was also affected by these parameters. Among the morphological subtypes of Pattern 4, recurrence-free survival decreased as the incidence of cribriform glands increased (P < .001).

CONCLUSION

Histopathological evaluation is important in predicting BCR in prostate adenocarcinoma, the Group Grade system seems to be helpful in this regard. More studies are needed to prove the relatively worse prognostic effect of cribriform glands.

Pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI in PI-RADS category 3 peripheral zone lesions: preliminary study evaluating DCE-MRI as an imaging biomarker for detection of clinically significant prostate cancers

PURPOSE

To determine if pharmacokinetic modeling of DCE-MRI can diagnose CS-PCa in PI-RADS category 3 PZ lesions with subjective negative DCE-MRI.

MATERIALS AND METHODS

In the present IRB approved, bi-institutional, retrospective, case-control study, we identified 73 men with 73 PZ PI-RADS version 2.1 category 3 lesions with MRI-directed-TRUS-guided targeted biopsy yielding: 12 PZ CS-PCa (ISUP Grade Group 2; N = 9, ISUP 3; N = 3), 27 ISUP 1 PCa and 34 benign lesions. An expert blinded radiologist segmented lesions on ADC and DCE images; segmentations were overlayed onto pharmacokinetic DCE-MRI maps. Mean values were compared between groups using univariate analysis. Diagnostic accuracy was assessed by ROC.

RESULTS

There were no differences in age, PSA, PSAD or clinical stage between groups (p = 0.265-0.645). Mean and 10th percentile ADC did not differ comparing CS-PCa to ISUP 1 PCa and benign lesions (p = 0.376 and 0.598) but was lower comparing ISUP ≥ 1 PCa to benign lesions (p < 0.001). Mean Ktrans (p = 0.003), Ve (p = 0.003) but not Kep (p = 0.387) were higher in CS-PCa compared to ISUP 1 PCa and benign lesions. There were no differences in DCE-MRI metrics comparing ISUP ≥ 1 PCa and benign lesions (p > 0.05). AUC for diagnosis of CS-PCa using Ktrans and Ve were: 0.69 (95% CI 0.52-0.87) and 0.69 (0.49-0.88).

CONCLUSION

Pharmacokinetic modeling of DCE-MRI parameters in PI-RADS category 3 lesions with subjectively negative DCE-MRI show significant differences comparing CS-PCa to ISUP 1 PCa and benign lesions, in this study outperforming ADC. Studies are required to further evaluate these parameters to determine which patients should undergo targeted biopsy for PI-RADS 3 lesions.

Algorithms applied to spatially registered multi-parametric MRI for prostate tumor volume measurement

Background

Prostate tumor volume correlates with critical components of cancer staging such as Gleason score (GS) grade, predicted disease progression, and metastasis. Therefore, non-invasive tumor volume measurement may elevate clinical management. Radiology assessments of multi-parametric MRI (MP-MRI) commonly visually examine individual images to determine possible tumor presence. This study combines registered MP-MRI into a single image that display normal tissue and possible lesions. This study tests and exploits the vector nature of spatially registered MP-MRI by using supervised target detection algorithms (STDA) and color display and psychovisual analysis (CIELAB) to non-invasively estimate prostate tumor volume.

Methods

MRI, including T1, T2, diffusion [apparent diffusion coefficient (ADC)], dynamic contrast enhanced (DCE) images, were resampled, rescaled, translated, and stitched to form spatially registered Multi-parametric cubes. The multi-parametric or multi-spectral signatures (7-component or T1, T2, ADC, etc.) that characterize the prostate tumors were inserted into target detection algorithms with conical decision surfaces (adaptive cosine estimator, ACE). Various detection thresholds were applied to discriminate tumor from normal tissue. In addition, tumor appeared as yellow in color images that were created by assigning red to washout from DCE, green to high B from diffusion, and blue to autonomous diffusion image. The yellow voxels in the three-channel hypercube were visually identified by a reader and recording voxels that exceed a threshold in the b* component of the CIELAB algorithm. The number of reported tumor voxels were converted to volume based on spatial resolution and slice separation. The tumor volume measurements were quantitatively validated by comparing the tumor volume computations to the pathologist's assessment of the histology of sectioned whole mount prostates from 26 consecutive patients with prostate adenocarcinoma who underwent radical prostatectomy. This study analyzed tumors exceeding 1 cc and that also took up contrast material (18 patients).

Results

High correlation coefficients for tumor volume measurements using supervised target detection and color analysis vs. histology from wholemount prostatectomy were computed (R=0.83 and 0.91, respectively). A linear fit for tumor volume measurements using for supervised target detection and color analysis vs. tumor measurements from radical prostatectomy (after correcting for shrinkage from the radical prostatectomy) results in a slope of 1.02 and 3.02, respectively. A polynomial fit for the color analysis to the histology found (R=0.95). Voxels exceeding a threshold in the b* part of the CIELAB algorithm yielded correlation coefficients (0.71, 0.80) offsets (0.01 cc, -0.63 cc) and slopes (1.99, 0.89) against the wholemount prostatectomy and color analysis, respectively.

Conclusions

Supervised target detection and color display and analysis applied to registered MP-MRI non-invasively estimates prostate tumor volumes >1 cc and displaying angiogenesis.

Prostate cancer measurements on serial MRI during active surveillance: it's time to be PRECISE

OBJECTIVE

The PRECISE criteria for reporting multiparametric MRI in patients on active surveillance (AS) for prostate cancer (PCa) score the likelihood of clinically significant change over time using a 1-5 scale, where 4 or 5 indicates radiological progression. According to the PRECISE recommendations, the index lesion size can be reported using different definitions of volume (planimetry or ellipsoid formula) or by measuring one or two diameters. We compared different measurements using planimetry as the reference standard and stratified changes according to the PRECISE scores.

METHODS

We retrospectively analysed 196 patients on AS with PCa confirmed by targeted biopsy who had two MR scans (baseline and follow-up). Lesions were measured on T₂ weighted imaging (T₂WI) according to all definitions. A PRECISE score was assessed for each patient.

RESULTS

The ellipsoid formula exhibited the highest correlation with planimetry at baseline (ρ = 0.97) and follow-up (ρ = 0.98) imaging, compared to the biaxial measurement and single maximum diameter. There was a significant difference (p < 0.001) in the yearly percentage volume change between radiological regression/stability (PRECISE 2-3) and progression (PRECISE 4-5) for planimetry (39.64%) and for the ellipsoid formula (46.78%).

CONCLUSION

The ellipsoid formula could be used to monitor tumour growth during AS. Evidence of a significant yearly percentage volume change between radiological regression/stability (PRECISE 2-3) and progression (PRECISE 4-5) has been also observed.

ADVANCES IN KNOWLEDGE

The ellipsoid formula is a reasonable surrogate for planimetry in capturing tumour volume changes on T₂WI in patients on imaging-led AS. This is also associated with radiological changes using the PRECISE recommendations.

Quantitative Prostate MRI

Prostate MRI is reported in clinical practice using the Prostate Imaging and Data Reporting System (PI-RADS). PI-RADS aims to standardize, as much as possible, the acquisition, interpretation, reporting, and ultimately the performance of prostate MRI. PI-RADS relies upon mainly subjective analysis of MR imaging findings, with very few incorporated quantitative features. The shortcomings of PI-RADS are mainly: low-to-moderate interobserver agreement and modest accuracy for detection of clinically significant tumors in the transition zone. The use of a more quantitative analysis of prostate MR imaging findings is therefore of interest. Quantitative MR imaging features including: tumor size and volume, tumor length of capsular contact, tumor apparent diffusion coefficient (ADC) metrics, tumor T₁ and T₂ relaxation times, tumor shape, and texture analyses have all shown value for improving characterization of observations detected on prostate MRI and for differentiating between tumors by their pathological grade and stage. Quantitative analysis may therefore improve diagnostic accuracy for detection of cancer and could be a noninvasive means to predict patient prognosis and guide management. Since quantitative analysis of prostate MRI is less dependent on an individual users' assessment, it could also improve interobserver agreement. Semi- and fully automated analysis of quantitative (radiomic) MRI features using artificial neural networks represent the next step in quantitative prostate MRI and are now being actively studied. Validation, through high-quality multicenter studies assessing diagnostic accuracy for clinically significant prostate cancer detection, in the domain of quantitative prostate MRI is needed. This article reviews advances in quantitative prostate MRI, highlighting the strengths and limitations of existing and emerging techniques, as well as discussing opportunities and challenges for evaluation of prostate MRI in clinical practice when using quantitative assessment. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

How accurately can multiparametric magnetic resonance imaging measure the tumour volume of a prostate cancer? Results of a systematic review

The tumour volume of a cancer within the prostate gland is commonly measured with multiparametric MRI. The measurement has a role in many clinical scenarios including focal therapy, but the accuracy of it has never been systematically reviewed. We included articles if they compared tumour volume measurements obtained by mpMRI with a reference volume measurement obtained after radical prostatectomy. Correlation and concordance statistics were summarised. A simple accuracy score was derived by dividing the given mean or median mpMRI volume by the histopathological reference volume. Factors affecting the accuracy were noted. Scores for potential bias and quality were calculated for each article. A total of 18 articles describing 1438 patients were identified. Nine articles gave Pearson's correlation scores, with a median value of 0.75 but the range was wide (0.42-0.97). A total of 11 articles reported mean values for volume while 9 reported median values. For all 18 articles, the mean or median values for MRI volumes were lower than the corresponding reference values suggesting consistent underestimation. For articles reporting mean and median values for volume, the median accuracy scores were 0.83 and 0.80, respectively. The accuracy was higher for tumours of greater volume, higher grade and when an endorectal coil was used. Accuracy did not seem to improve over time, with a 3 Tesla magnet or by applying a shrinkage factor to the reference measurement. Most studies showed evidence of at least moderate bias, and their quality was highly variable, but neither of these appeared to affect accuracy.

Utility of index lesion volume assessed by multiparametric MRI combined with Gleason grade for assessment of lymph node involvement in patients with high-risk prostate cancer

PURPOSE

We examined the potential predictors of lymph node involvement and evaluated whether index lesion volume assessed using multiparametric magnetic resonance imaging is associated with lymph node involvement among patients with high-risk prostate cancer.

METHODS

Extended pelvic lymph node dissection was used to evaluate patients with lymph node involvement. We retrospectively analyzed consecutive 102 patients with high-risk prostate cancer who underwent extended pelvic lymph node dissection at our institution between 2011 and 2017. To evaluate the index lesion volume at multiparametric magnetic resonance imaging (mrV), lesions were manually contoured on each T2-weighted axial slice in combination with diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging and integrated using image analysis software. Logistic regression analysis was performed to identify predictors of lymph node involvement.

RESULTS

The median mrV was 1.4 ml (range 0-30.1 ml), and the median number of resected lymph nodes was 14 (range 7-38). Among 102 patients, 28 (28%) had lymph node involvement. Multivariate analysis identified significant predictors of lymph node involvement as follows: biopsy Gleason-grade group 5 (odds ratio = 17.2; 95% confidence interval, 2.1-299.0; P = 0.005), preoperative mrV (odds ratio = 1.14; 95% confidence interval, 1.02-1.30; P = 0.025) and percentage of positive cores with highest Gleason-grade group (odds ratio = 1.05; 95% confidence interval, 1.01-1.10; P = 0.005). Lymph node involvement was prevalent (69%) among tumors with Gleason-grade group 5 and mrV ≥3.4 ml, but was infrequently (10%) present among tumors with Gleason-grade group ≤4 and mrV <3.4 ml.

CONCLUSIONS

The combination of biopsy Gleason-grade and mrV may serve as a useful tool to stratify patients according to their risk of nodal metastases.

Effect of observation size and apparent diffusion coefficient (ADC) value in PI-RADS v2.1 assessment category 4 and 5 observations compared to adverse pathological outcomes

OBJECTIVE

To compare observation size and apparent diffusion coefficient (ADC) values in Prostate Imaging Reporting and Data System (PI-RADS) v2.1 category 4 and 5 observations to adverse pathological features.

MATERIALS AND METHODS

With institutional review board approval, 267 consecutive men with 3-T MRI before radical prostatectomy (RP) between 2012 and 2018 were evaluated by two blinded radiologists who assigned PI-RADS v2.1 scores. Discrepancies were resolved by consensus. A third blinded radiologist measured observation size and ADC (ADC.mean, ADC.min [lowest ADC within an observation], ADC.ratio [ADC.mean/ADC.peripheral zone {PZ}]). Size and ADC were compared to pathological stage and Gleason score (GS) using t tests, ANOVA, Pearson correlation, and receiver operating characteristic (ROC) analysis.

RESULTS

Consensus review identified 267 true positive category 4 and 5 observations representing 83.1% (222/267) PZ and 16.9% (45/267) transition zone (TZ) tumors. Inter-observer agreement for PI-RADS v2.1 scoring was moderate (K = 0.45). Size was associated with extra-prostatic extension (EPE) (19 ± 8 versus 14 ± 6 mm, p < 0.001) and seminal vesicle invasion (SVI) (24 ± 9 versus 16 ± 7 mm, p < 0.001). Size ≥ 15 mm optimized the accuracy for EPE with area under the ROC curve (AUC) and sensitivity/specificity of 0.68 (CI 0.62-0.75) and 63.2%/65.6%. Size ≥ 19 mm optimized the accuracy for SVI with AUC/sensitivity/specificity of 0.75 (CI 0.66-0.83)/69.4%/70.6%. ADC metrics were not associated with pathological stage. Larger observation size (p = 0.032), lower ADC.min (p = 0.010), and lower ADC.ratio (p = 0.010) were associated with higher GS. Size correlated better to higher Gleason scores (p = 0.002) compared to ADC metrics (p = 0.09-0.11).

CONCLUSION

Among PI-RADS v2.1 category 4 and 5 observations, size was associated with higher pathological stage whereas ADC metrics were not. Size, ADC.minimum, and ADC.ratio differed in tumors stratified by Gleason score.

KEY POINTS

• Among PI-RADS category 4 and 5 observations, size but not ADC can differentiate between tumors by pathological stage. • An observation size threshold of 15 mm and 19 mm optimized the accuracy for diagnosis of extra-prostatic extension and seminal vesicle invasion. • Among PI-RADS category 4 and 5 observations, size, ADC.minimum, and ADC.ratio differed comparing tumors by Gleason score.

Prognostic Value of Pretreatment MRI in Patients With Prostate Cancer Treated With Radiation Therapy: A Systematic Review and Meta-Analysis

OBJECTIVE. Despite a substantial increase in the use of MRI for pretreatment evaluation of prostate cancer, its prognostic value in patients undergoing radiation therapy (RT) is not well known. Therefore, the purpose of this study was to systematically review the literature and perform a meta-analysis on the prognostic value of pretreatment MRI in patients with prostate cancer who underwent external beam radiation therapy (EBRT) or brachytherapy. MATERIALS AND METHODS. PubMed and Embase databases were searched for studies published on or before March 13, 2019. We included studies that evaluated pretreatment MRI as a prognostic factor in prostate cancer regarding biochemical recurrence (BCR), metastatic failure, and overall or cancer-specific mortality. Effect sizes were measured in terms of the hazard ratio (HR) and were meta-analytically pooled using the random-effects model. The quality of the studies was independently evaluated using the Quality in Prognostic Studies tool. RESULTS. Twelve studies (2205 patients) were included. All studies assessed BCR; metastasis was evaluated in three studies, and mortality was evaluated in one study. Extraprostatic extension (EPE), seminal vesicle invasion (SVI), large tumor size or volume, number of sextants involved, and tumor involvement of prostatic apex were significant prognostic factors of BCR (pooled HRs = 1.50-4.47). EPE, larger tumor size, greater tumor volume, presence of metastatic pelvic lymph nodes (LNs), and presence of SVI were significant risk factors for metastasis (pooled HRs = 1.12-11.96). Pelvic LN metastasis was significantly predictive of cancer-specific mortality (HR = 4.45 [95% CI, 1.30-15.23]). CONCLUSION. Several pretreatment MRI findings were significant prognostic factors in patients with prostate cancer who underwent RT.

Index tumor volume on MRI as a predictor of clinical and pathologic outcomes following radical prostatectomy

PURPOSE

Index tumor volume (ITV) measured on radical prostatectomy (RP) specimens has been shown to be associated with adverse pathologic and oncologic outcomes. We evaluate the value of ITV calculated from prostate multiparametric MRI (mpMRI) in predicting adverse clinical and pathologic outcomes.

MATERIALS AND METHODS

Data from a prospectively maintained, single-institution database were analyzed for patients who underwent mpMRI prior to RP (2007-2016). Index tumor was defined as a T2-visible lesion with the longest diameter. Adverse pathologic outcomes were extraprostatic extension (EPE), lymph node invasion (LNI), seminal vesicle invasion (SVI), and positive margins (PM). Logistic and Cox proportional hazard regression were used to assess associations with adverse pathology and biochemical recurrence (BCR), respectively.

RESULTS

Of the 455 patients included, EPE, LNI, SVI and PM were present in 23.5%, 6.2%, 5.5% and 15.7% patients, respectively. Patients with adverse pathologic outcomes had larger median ITV. ITV was found to be an independent predictor of EPE (OR 1.22, p = 0.010), LNI (OR 1.39, p = 0.001), and SVI (OR 1.28, p = 0.009), but not PM (OR 1.03, p = 0.522). Combination of ITV and PSA was found to have predictive ability comparable to that of modified Partin tables (EPE:ITV + PSA_AUC = 0.71 vs. Partin_AUC = 0.71; LNI:ITV + PSA_AUC = 0.92 vs. Partin_AUC = 0.90, SVI:ITV + PSA_AUC = 0.78 vs. Partin_AUC = 0.82). 5 year BCR-free survival (median follow-up 24.9 months) was higher for patients with ITV < 2 cc (84.1% vs. 58.5%, p = 0.001). However, ITV was not found to be an independent predictor of BCR (HR 1.69, p = 0.130).

CONCLUSIONS

We demonstrate that ITV measured on mpMRI is a predictor of adverse pathologic and clinical outcomes and can aid in preoperative risk assessment.

Comparison of T2-Weighted Imaging, DWI, and Dynamic Contrast-Enhanced MRI for Calculation of Prostate Cancer Index Lesion Volume: Correlation With Whole-Mount Pathology

OBJECTIVE

The objective of our study was to investigate the comparative effectiveness of different MRI sequences for the estimation of index lesion volume in patients with prostate cancer (PCa) compared with ground truth volume measured on whole-mount pathology.

MATERIALS AND METHODS

Patients with PCa underwent multiparametric MRI (mpMRI) on a 3-T MRI scanner before radical prostatectomy. Forty PCa index lesions were identified and outlined on histology by a pathologist. Two radiologists who were informed about the presence of PCa but were not aware of lesion outlines on histology worked in consensus to delineate PCa lesions on T2-weighted imaging, apparent diffusion coefficient (ADC) maps, and early-phase dynamic contrast-enhanced MRI (DCE-MRI). The lesion volumes from different mpMRI sequences and the percentage of volume underestimation compared with pathology were calculated and correlated with volume at pathology. The repeated-measures ANOVA with the posthoc Bonferroni test was performed to evaluate whether the difference between the estimated tumor volumes was statistically significant.

RESULTS

The mean PCa lesion volume estimated from pathology, T2-weighted imaging, DWI (ADC maps), and DCE-MRI were 4.61 ± 4.99 (SD) cm³, 2.03 ± 2.96 cm³, 1.81 ± 2.76 cm³, and 3.48 ± 4.06 cm³, respectively. The lesion volumes on T2-weighted images (p = 0.000002), ADC maps (p = 0.000003), and DCE-MR images (p = 0.004412) were significantly lower than those from pathology. PCa lesion volume was significantly underestimated on T2-weighted images, ADC maps, and DCE-MR images compared with pathology by 54.98% ± 22.60% (mean ± SD), 58.59% ± 18.58%, and 18.33% ± 30.11%, respectively; underestimation using T2-weighted imaging (p = 1.01 × 10^-11) and DWI (p = 2.94 × 10^-11) was significantly higher than underestimation using DCE-MRI. Correlations between lesion volume estimated on T2-weighted images, ADC maps, and DCE-MR images with pathology were 0.91 (p = 9.03 × 10^-16), 0.86 (p = 7.32 × 10^-13), and 0.93 (p = 8.22 × 10^-18), respectively.

CONCLUSION

DCE-MRI performed better than T2-weighted imaging and DWI for estimation of index PCa volume and therefore can be preferred over these other two sequences for volume estimation.

Large-Gland Proliferations of the Prostate

Large-gland proliferations of the prostate have gained considerable attention in the past decade. The differential diagnosis is quite broad but can be refined using histologic criteria and, sometimes, immunostains. Pathologists have come to realize that cribriform and intraductal as well as ductal carcinomas are particularly aggressive patterns, and should name them in diagnostic reporting when present.

Prospective comparison of PI-RADS version 2 and qualitative in-house categorization system in detection of prostate cancer

BACKGROUND

Prostate Imaging-Reporting and Data System v. 2 (PI-RADSv2) provides standardized nomenclature for interpretation of prostate multiparametric MRI (mpMRI). Inclusion of additional features for categorization may provide benefit to stratification of disease.

PURPOSE

To prospectively compare PI-RADSv2 to a qualitative in-house system for detecting prostate cancer on mpMRI.

STUDY TYPE

Prospective.

POPULATION

In all, 338 patients who underwent mpMRI May 2015-May 2016, with subsequent MRI/transrectal ultrasound fusion-guided biopsy.

FIELD STRENGTH

3T mpMRI (T2 W, diffusion-weighted [DW], apparent diffusion coefficient [ADC] map, b-2000 DWI acquisition, and dynamic contrast-enhanced [DCE] MRI).

ASSESSMENT

One genitourinary radiologist prospectively read mpMRIs using both in-house and PI-RADSv2 5-category systems.

STATISTICAL TEST

In lesion-based analysis, overall and clinically significant (CS) tumor detection rates (TDR) were calculated for all PI-RADSv2 and in-house categories. The ability of each scoring system to detect cancer was assessed by area under receiver operator characteristic curve (AUC). Within each PI-RADSv2 category, lesions were further stratified by their in-house categories to determine if TDRs can be increased by combining features of both systems.

RESULTS

In 338 patients (median prostate-specific antigen [PSA] 6.5 [0.6-113.6] ng/mL; age 64 [44-84] years), 733 lesions were identified (47% tumor-positive). Predictive abilities of both systems were comparable for all (AUC 76-78%) and CS cancers (AUCs 79%). The in-house system had higher overall and CS TDRs than PI-RADSv2 for categories 3 and 4 (P < 0.01 for both), with the greatest difference between the scoring systems seen in lesions scored category 4 (CS TDRs: in-house 65%, PI-RADSv2 22.1%). For lesions categorized as PI-RADSv2 = 4, characterization of suspicious/indeterminate extraprostatic extension (EPE) and equivocal findings across all mpMRI sequences contributed to significantly different TDRs for both systems (TDR range 19-75%, P < 0.05).

DATA CONCLUSION

PI-RADSv2 behaves similarly to an existing validated system that relies on the number of sequences on which a lesion is seen. This prospective evaluation suggests that sequence positivity and suspicion of EPE can enhance PI-RADSv2 category 4 cancer detection.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1326-1335.

Pathological tumor volume predicts survival outcomes in oral squamous cell carcinoma

The present study examined whether the pathological tumor volume (PTV) was correlated with the survival outcomes in patients with oral squamous cell carcinoma (SCC) and clinical lymph node metastasis. Forty-seven patients who underwent radical surgery without preoperative treatment were enrolled. The PTV of the primary tumor, which was surgically resected without preoperative treatment, was calculated based on the diameters in three dimensions. A survival analysis was performed using a Cox proportional hazards model. A PTV of ≥18 cm³ was significantly correlated with shorter overall survival (P<0.01) and local recurrence-free survival (P<0.01) in a univariate analysis. A multivariate analysis with adjustment for the pathological stage (stage I–II/III–IV), primary site (tongue/others) and positive surgical margin and/or extracapsular extension (absent/present) showed that a PTV of ≥18 cm³ was significantly correlated with shorter overall survival (P<0.01) and local recurrence-free survival (P<0.01). The present findings suggested that PTV in oral SCC provides a prognostic parameter that may predict shorter or longer overall and local recurrence-free survival.

Surgical margin status and its impact on prostate cancer prognosis after radical prostatectomy: a meta-analysis

Background and purpose

Positive surgical margins (PSMs) correlate with adverse outcomes in numerous solid tumours. However, the prognostic value of PSMs in prostate cancer (PCa) patients who underwent radical prostatectomy remains unclear. Herein, we performed a meta-analysis to evaluate the association between PSMs and the prognostic value for biochemical recurrence-free survival (BRFS), cancer-specific survival (CSS), overall survival (OS), cancer-specific mortality (CSM) and overall mortality (OM) in PCa patients.

Materials and methods

According to the PRISMA statement, online databases PubMed, EMBASE and Web of Science were searched to identify relevant studies published prior to February 2018. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated to evaluate the relationship between PSMs and PCa.

Results

Ultimately, 32 cohort studies that met the eligibility criteria and involved 141,222 patients (51–65,633 per study) were included in this meta-analysis. The results showed that PSMs were significantly predictive of poorer BRFS (HR = 1.35, 95% CI 1.28–1.48, p < 0.001), CSS (HR = 1.49, 95% CI 1.16–1.90, p = 0.001) and OS (HR = 1.11, 95% CI 1.02–1.20, p = 0.014). In addition, PSMs were significantly associated with higher risk of CSM (HR = 1.23, 95% CI 1.16–1.30, p < 0.001) and OM (HR = 1.09, 95% CI 1.02–1.16, p = 0.009) in patients with PCa.

Conclusions

Our study suggests that the presence of a histopathologic PSM is associated with the clinical outcomes BRFS, CSS, OS, CSM and OM in patients with PCa, and PSMs could serve as a poor prognostic factor for patients with PCa.

Electronic supplementary material

The online version of this article (10.1007/s00345-018-2333-4) contains supplementary material, which is available to authorized users.

A novel biopsy-related parameter derived from location and relationship of positive cores on standard 12-core trans-rectal ultrasound-guided prostate biopsy: a useful parameter for predicting tumor volume compared to number of positive cores

PURPOSE

To develop a novel biopsy-related parameter, named overlapping line, defined as the line between the adjacent positive cores on 12-core trans-rectal ultrasound-guided prostate biopsy, and evaluated the value of overlapping line for predicting tumor volume in the final pathologic examination.

METHODS

Among patients with prostate cancer who underwent radical prostatectomy at Boramae Medical Center, 470 patients who underwent standard 12-core trans-rectal ultrasound-guided prostate biopsy were selected for the analysis. The number of overlapping line was determined in each patient, and its effects on tumor volume were evaluated after adjusting for other variables.

RESULTS

Median prostate specific antigen level was 9.1 ng/mL, and the maximum % cancer in positive cores was 42.8%. Median numbers of positive cores and overlapping lines were three and two, respectively. The pathologic stage was T2 or less, T3a, and T3b or greater in 297 (63.5%), 104 (22.2%), and 67 patients (14.3%), respectively. Median tumor volume in prostatectomy specimen was 3.4 mL. In multivariable analysis, the number of overlapping lines (B 0.750, p < 0.001) was a significant predictor for tumor volume, in addition to prostate specific antigen level and maximum % cancer in positive cores. In addition, the model with overlapping line showed superior accuracy compared to the model with positive core based adjusted r ² (0.467 vs. 0.456).

CONCLUSIONS

The number of overlapping lines, a novel prostate biopsy-related variable, is thought to be a more reliable predictor for tumor volume compared to the number of positive cores and could be easily applied to routine daily practice.

Tumor Volume and Clinical Failure in High-Risk Prostate Cancer Patients Treated With Radical Prostatectomy

INTRODUCTION

To identify the most significant cut-off of tumor volume (TV) for prediction of clinical failure (CF) among high-risk prostate cancer (hPCa) patients.

METHODS

Within a multi-institutional cohort, 262 patients treated with radical prostatectomy (RP) for hPCa were identified. CF was defined as local recurrence or distant metastases. A time dependent ROC curve was used to evaluate the area under the curve (AUC) using TV as single marker to predict clinical failure at 10 years. We searched for the TV cut off value with the highest combined sensitivity and specificity predicting CF. Three multivariable Cox regression analyses (MVA) tested the predictors of CF after RP. Predictors of the model 1 were pre-operative PSA, pathologic stage (PT), pathologic Gleason sum (GS), surgical margin status, and lymph node invasion. Predictors of the models 2 and 3 were the same of model 1 plus TV as a continuous or dichotomous variable using the defined cutoff, respectively. Validation (leave-one-out-cross-validation-LOOCV) of each model was performed.

RESULTS

Overall, 46 (17.6%) patients experienced CF. The TV value was 6.29 ml. In MVA of models 2 and 3, PT and GS remained independent predictors of CF. Moreover, in model 2 TV (HR:1.07,) and in model 3 TV >6.29 ml (HR:2.99,) were independently associated with CF. In LOOCV, the C-index of models 1-3 were 65.53%, 71.75%, and 70.26%, respectively.

CONCLUSIONS

TV is an independent predictor of CF in hPCa patients. Patients with a TV exceeding the cut-off of 6.29 ml are more likely to develop CF. Prostate 77:3-9, 2017. © 2016 Wiley Periodicals, Inc.

Effect of Preoperative Risk Group Stratification on Oncologic Outcomes of Patients with Adverse Pathologic Findings at Radical Prostatectomy

Background

Current National Comprehensive Cancer Network guidelines recommend postoperative radiation therapy based only on adverse pathologic findings (APFs), irrespective of preoperative risk group. We assessed whether a model incorporating both the preoperative risk group and APFs could predict long-term oncologic outcomes better than a model based on APFs alone.

Methods

We retrospectively reviewed 4,404 men who underwent radical prostatectomy (RP) at our institution between 1992 and 2014. After excluding patients receiving neoadjuvant therapy or with incomplete pathological or follow-up data, 3,092 men were included in the final analysis. APFs were defined as extraprostatic extension (EPE), seminal vesicle invasion (SVI), or a positive surgical margin (PSM). The adequacy of model fit to the data was compared using the likelihood-ratio test between the models with and without risk groups, and model discrimination was compared with the concordance index (c-index) for predicting biochemical recurrence (BCR) and prostate cancer-specific mortality (PCSM). We performed multivariate Cox proportional hazard model and competing risk regression analyses to identify predictors of BCR and PCSM in the total patient group and each of the risk groups.

Results

Adding risk groups to the model containing only APFs significantly improved the fit to the data (likelihood-ratio test, p <0.001) and the c-index increased from 0.693 to 0.732 for BCR and from 0.707 to 0.747 for PCSM. A RP Gleason score (GS) ≥8 and a PSM were independently associated with BCR in the total patient group and also each risk group. However, only a GS ≥8 and SVI were associated with PCSM in the total patient group (GS ≥8: hazard ratio [HR] 5.39 and SVI: HR 3.36) and the high-risk group (GS ≥8: HR 6.31 and SVI: HR 4.05).

Conclusion

The postoperative estimation of oncologic outcomes in men with APFs at RP was improved by considering preoperative risk group stratification. Although a PSM was an independent predictor for BCR, only a RP GS ≥8 and SVI were associated with PCSM in the total patient and high-risk groups.

Multiparametric magnetic resonance imaging and frozen-section analysis efficiently predict upgrading, upstaging, and extraprostatic extension in patients undergoing nerve-sparing robotic-assisted radical prostatectomy

To evaluate the role of multiparametric magnetic resonance imaging (mpMRI) in predicting upgrading, upstaging, and extraprostatic extension in patients with low-risk prostate cancer (PCa). MpMRI may reduce positive surgical margins (PSM) and improve nerve-sparing during robotic-assisted radical prostatectomy (RARP) for localized prostate cancer PCa.This was a retrospective, monocentric, observational study. We retrieved the records of patients undergoing RARP from January 2012 to December 2013 at our Institution. Inclusion criteria were: PSA <10 ng/mL; clinical stage <T3a; biopsy Gleason score <7; prostate mpMRI performed preoperatively at our Institution; intraoperative FSA of the posterolateral aspects of the specimen.All the identified lesions were scored according to the Prostate Imaging Reporting and Data System (PIRADS). We considered the lesion with the highest PIRADS score as index lesion. All the included patients underwent nerve-sparing RARP. During surgery, the specimen was sent for FSA of the posterolateral aspects. The surgeon, according to the localization scheme provided by the mpMRI, inked the region of the posterolateral aspect of the prostate that had to be submitted to FSA.We evaluated association between clinical features and PSM, upgrading, upstaging, and presence of unfavorable disease.Two hundred fifty-four patients who underwent nerve-sparing RARP were included. PSM rate was 29.13% and 15.75% at FSA and final pathology respectively. Interestingly, the use of FSA reduced PSM rate in pT3 disease (25.81%). Higher PIRADS scores demonstrated to be related to high probability of upgrading and upstaging. This significativity remains even when considering PIRADS 2-3 versus 4 versus 5 and PIRADS 2-3 versus 4-5. Also PSM at FSA were associated with higher probability of upgrading and upstaging.PIRADS score and FSA resulted to be strictly related to grading and staging, thus being able to predict upgrading and/or upstaging at final pathology.

Prostate cancer volume estimations based on transrectal ultrasonography-guided biopsy in order to predict clinically significant prostate cancer

INTRODUCTION

Tumor diameter is a reliable parameter to estimate tumor volume in solid organ cancers; its use in prostate cancer is controversial since it exhibits a more irregular pattern of growth. This study aimed to examine the association between the tumor volume estimations based on transrectal ultrasound (TRUS) guided biopsy results and the tumor volume measured on the pathological specimen.

MATERIALS AND METHODS

A total of 237 patients who underwent radical retropubic prostatectomy (RRP) were included in this retrospective study. The differences and correlations between cancer volume estimations based on TRUS guided biopsy findings and cancer volume estimations based on post-prostatectomy pathology specimens were examined. In addition, diagnostic value of TRUS guided biopsy-based volume estimations in order to predict clinically significant cancer (>0.5 cc) were calculated.

RESULTS

The mean cancer volume estimated using TRUS biopsy results was lower (5.5±6.5 cc) than the mean cancer volume calculated using prostatectomy specimens (6.4±7.6 cc) (p<0.041).TRUS guided biopsy examination resulted in 5 false positive and 15 false negative cases. There was a significant but weak correlation between the two parameters (r=0.62, p<0.001). The sensitivity and specificity of TRUS guided biopsy in predicting the presence of clinically significant cancer was 93.4% (95% CI, 89.1-96.1) and 50.0% (95% CI, 20.1-79.9), respectively.

CONCLUSIONS

TRUS guided biopsy-derived estimations seem to have a limited value to predict pathologically established tumor volume. Further studies are warranted to identify additional methods that may more accurately predict actual pathological characteristics and prognosis of prostate cancer.

Association between very small tumour size and increased cancer-specific mortality after radical prostatectomy in lymph node-positive prostate cancer

OBJECTIVE

To determine whether very small prostate cancers present in patients who also have lymph node (LN) metastases represent a particularly aggressive disease variant compared with larger LN-positive tumours.

PATIENTS AND METHODS

We identified 37 501 patients diagnosed with prostate cancer between 1988 and 2001 treated with radical prostatectomy within the Surveillance, Epidemiology, and End Results database. The primary study variables were tumour size by largest dimension (stratified into: (i) microscopic focus only or 1 mm; (ii) 2-15 mm; (iii) 16-30 mm; (iv) >30 mm), regional LN involvement, and the corresponding interaction term. We evaluated the risk of 10-year prostate cancer-specific mortality (PCSM) using the Fine and Gray model for competing risks after controlling for race, tumour grade, T stage, receipt of radiation, number of dissected LNs, number of positive LNs, year of diagnosis, and age at diagnosis.

RESULTS

The median follow-up was 11.8 years. There was a significant interaction between tumour size and LN involvement (P-interaction <0.001). In the absence of LN involvement (36 561 patients), the risk of 10-year PCSM increased monotonically with increasing tumour size. Among patients with LN involvement (940), those with the smallest tumours had increased 10-year PCSM compared with patients with tumours sized 2-15 mm (24.7% vs 11.8%; adjusted hazard ratio [AHR] 2.84, 95% confidence interval [CI] 1.21-6.71; P = 0.017) or 16-30 mm (24.7% vs 15.5%; AHR 3.12, 95% CI 1.51-6.49; P = 0.002), and similar 10-year PCSM as those with tumours >30 mm (24.7% vs 24.9%; P = 0.156).

CONCLUSION

In patients with prostate cancer with LN involvement, very small tumour size may predict for higher PCSM compared with some larger tumours, even after controlling for other prognostic variables. These tumours might be particularly aggressive, beyond what is captured by pathological assessment of tumour grade and stage.

How accurate is multiparametric MR imaging in evaluation of prostate cancer volume?

PURPOSE

To assess the factors influencing multiparametric (MP) magnetic resonance (MR) imaging accuracy in estimating prostate cancer histologic volume (Vh).

MATERIALS AND METHODS

A prospective database of 202 patients who underwent MP MR imaging before radical prostatectomy was retrospectively used. Institutional review board approval and informed consent were obtained. Two independent radiologists delineated areas suspicious for cancer on images (T2-weighted, diffusion-weighted, dynamic contrast material-enhanced [DCE] pulse sequences) and scored their degree of suspicion of malignancy by using a five-level Likert score. One pathologist delineated cancers on whole-mount prostatectomy sections and calculated their volume by using digitized planimetry. Volumes of MR true-positive lesions were measured on T2-weighted images (VT2), on ADC maps (VADC), and on DCE images [VDCE]). VT2, VADC, VDCE and the greatest volume determined on images from any of the individual MR pulse sequences (Vmax) were compared with Vh (Bland-Altman analysis). Factors influencing MP MR imaging accuracy, or A, calculated as A = Vmax/Vh, were evaluated using generalized linear mixed models.

RESULTS

For both readers, Vh was significantly underestimated with VT2 (P < .0001, both), VADC (P < .0001, both), and VDCE (P = .02 and P = .003, readers 1 and 2, respectively), but not with Vmax (P = .13 and P = .21, readers 1 and 2, respectively). Mean, 25th percentile, and 75th percentile, respectively, for Vmax accuracy were 0.92, 0.54, and 1.85 for reader 1 and 0.95, 0.57, and 1.77 for reader 2. At generalized linear mixed (multivariate) analysis, tumor Likert score (P < .0001), Gleason score (P = .009), and Vh (P < .0001) significantly influenced Vmax accuracy (both readers). This accuracy was good in tumors with a Gleason score of 7 or higher or a Likert score of 5, with a tendency toward underestimation of Vh; accuracy was poor in small (<0.5 cc) or low-grade (Gleason score ≤6) tumors, with a tendency toward overestimation of Vh.

CONCLUSION

Vh can be estimated by using Vmax in aggressive tumors or in tumors with high Likert scores.