Evaluation of the normal-to-diseased apparent diffusion coefficient ratio as an indicator of prostate cancer aggressiveness

Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners

Background

MRI is an important tool in the prostate cancer work-up, with special emphasis on the ADC sequence. This study aimed to investigate the correlation between ADC and ADC ratio compared to tumor aggressiveness determined by a histopathological examination after radical prostatectomy.

Methods

Ninety-eight patients with prostate cancer underwent MRI at five different hospitals prior to radical prostatectomy. Images were retrospectively analyzed individually by two radiologists. The ADC of the index lesion and reference tissues (contralateral normal prostatic, normal peripheral zone, and urine) was recorded. Absolute ADC and different ADC ratios were compared to tumor aggressivity according to the ISUP Gleason Grade Groups extracted from the pathology report using Spearman's rank correlation coefficient (ρ). ROC curves were used to evaluate the ability to discriminate between ISUP 1-2 and ISUP 3-5 and intra class correlation and Bland-Altman plots for interrater reliability.

Results

All patients had prostate cancer classified as ISUP grade ≥ 2. No correlation was found between ADC and ISUP grade. We found no benefit of using the ADC ratio over absolute ADC. The AUC for all metrics was close to 0.5, and no threshold could be extracted for prediction of tumor aggressivity. The interrater reliability was substantial to almost perfect for all variables analyzed.

Conclusions

ADC and ADC ratio did not correlate with tumor aggressiveness defined by ISUP grade in this multicenter MRI study. The result of this study is opposite to previous research in the field.

Do the variations in ROI placement technique have influence for prostate ADC measurements?

Background

Prostate apparent diffusion coefficient (ADC) values calculated from diffusion-weighted imaging have been used for evaluating prostate cancer (PCa) aggressiveness. However, the way of measuring ADC values has varied depending on the study.

Purpose

To investigate inter- and intra-reader variability and diagnostic performance of three kinds of shaped 2D regions of interests (ROIs) for tumor ADC measurements in PCa.

Material and Methods

Seventy-four patients with PCa undergoing 3-T MRI before surgery were included. Histologic findings from radical prostatectomy specimens were reviewed to define each patient’s dominant tumor. Three readers independently measured the tumor ADCs using three different ROI methods: freehand, large-circle, and small-circles ROIs. Readers repeated measurements after 3 weeks. Bland-Altman analysis was performed to evaluate the inter- and intra-reader variability. Receiver Operating Characteristic analysis was used for assessment of tumor aggressiveness for PCa.

Results

For intra-reader and inter-reader variability, the mean coefficient of repeatability for freehand ROIs, large-circle ROIs, and small-circles ROIs were as follows: 13.7%, 12.4%, and 11.5%; 9.4%, 9.7%, and 9.5%. For differentiating Gleason score (GS) = 3 + 3 from GS ≥ 3 + 4 tumors, the area under the curves were 0.90 for freehand ROIs, 0.89 for large-circle ROIs, and 0.94 small-circles ROIs ( p = 0.31).

Conclusion

The variations in ROI method did not have a major influence on intra-reader or inter-reader reproducibility or diagnostic performance for prostate ADC measurements.

Prostate Cancer Diffusion-Weighted Magnetic Resonance Imaging: Does the Choice of Diffusion-Weighting Level Matter?

BACKGROUND

Diffusion-weighted magnetic resonance imaging plays an important role in multiparametric assessment of prostate lesions. The derived apparent diffusion coefficient (ADC) could be a useful quantitative biomarker for malignant growth, but lacks acceptance because of low reproducibility.

PURPOSE

To investigate the impact of the choice of diffusion-weighting levels (b-values) on contrast-to-noise ratio and quantitative measures in prostate diffusion-weighted MRI.

STUDY TYPE

Retrospective and simulation based on published data.

SUBJECTS

Patient cohort (21 men with Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score ≥3) from a single-center study.

FIELD STRENGTH/SEQUENCE

3 T/diffusion-weighted imaging with single-shot echo-planar imaging.

ASSESSMENT

Both clinical data and simulations based on previously acquired data were used to quantify the influence of b-value choice in normal peripheral zone (PZ) and PZ tumor lesions. For clinical data, ADC was determined for different combinations of b-values. Contrast-to-noise ratio and quantitative diffusion measures were simulated for a wide range of b-values.

STATISTICAL TESTS

Tissue ADC and the lesion-to-normal tissue ADC ratios of different b-value combinations were compared with paired two-tailed Student's t-tests. A P-value <0.05 was considered statistically significant.

RESULTS

Findings about b-value dependence derived from clinical data and from simulations agreed with each other. Provided measurement was limited to two b-values, simulation-derived optimal b-value choices coincided with PI-RADSv2 recommendations. For two-point measurements, ADC decreased by 15% when the maximum b-value increased from 1000 to 1500 seconds/mm² , but corresponding lesion-to-normal tissue ADC ratio showed no significant change (P = 0.86 for acquired data). Simulations with three or more measurement points produced ADCs that declined by only 8% over this range of maximum b-value. Corresponding ADC ratios declined between 2.6% (three points) and 3.8% (21 points). Simulations also revealed an ADC reduction of about 19% with the shorter echo and diffusion time evaluated.

DATA CONCLUSION

The comprehensive assessment of b-value dependence permits better formulation of protocol and analysis recommendations for obtaining reproducible results in prostate cancer diffusion-weighted MRI.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

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.

Prostate cancer GTV delineation with biparametric MRI and 68Ga-PSMA-PET: comparison of expert contours and semi-automated methods

OBJECTIVE

The optimal method for delineation of dominant intraprostatic lesions (DIL) for targeted radiotherapy dose escalation is unclear. This study evaluated interobserver and intermodality variability of delineations on biparametric MRI (bpMRI), consisting of T₂ weighted (T₂W) and diffusion-weighted (DWI) sequences, and ⁶⁸Ga-PSMA-PET/CT; and compared manually delineated GTV contours with semi-automated segmentations based on quantitative thresholding of intraprostatic apparent diffusion coefficient (ADC) and standardised uptake values (SUV).

METHODS

16 patients who had bpMRI and PSMA-PET scanning performed prior to any treatment were eligible for inclusion. Four observers (two radiation oncologists, two radiologists) manually delineated the DIL on: (1) bpMRI (GTV_MRI), (2) PSMA-PET (GTV_PSMA) and (3) co-registered bpMRI/PSMA-PET (GTV_Fused) in separate sittings. Interobserver, intermodality and semi-automated comparisons were evaluated against consensus Simultaneous Truth and Performance Level Estimation (STAPLE) volumes, created from the relevant manual delineations of all observers with equal weighting. Comparisons included the Dice Similarity Coefficient (DSC), mean distance to agreement (MDA) and other metrics.

RESULTS

Interobserver agreement was significantly higher (p < 0.05) for GTV_PSMA (DSC: 0.822, MDA: 1.12 mm) and GTV_Fused (DSC: 0.787, MDA: 1.34 mm) than for GTV_MRI (DSC: 0.705, MDA 2.44 mm). Intermodality agreement between GTV_MRI and GTV_PSMA was low (DSC: 0.440, MDA: 4.64 mm). Agreement between semi-automated volumes and consensus GTV was low for MRI (DSC: 0.370, MDA: 8.16 mm) and significantly higher for PSMA-PET (0.571, MDA: 4.45 mm, p < 0.05).

CONCLUSION

⁶⁸Ga-PSMA-PET appears to improve interobserver consistency of DIL localisation vs bpMRI and may be more viable for simple quantitative delineation approaches; however, more sophisticated approaches to semi-automatic delineation factoring for patient- and disease-related heterogeneity are likely required.

ADVANCES IN KNOWLEDGE

This is the first study to evaluate the interobserver variability of prostate GTV delineations with co-registered bpMRI and ⁶⁸Ga-PSMA-PET.

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.

Biparametric versus multiparametric magnetic resonance imaging of the prostate: detection of clinically significant cancer in a perfect match group

Background

Biparametric (bp) magnetic resonance imaging (MRI) could be an alternative MRI for the detection of the clinically significant prostate cancer (csPCa).

Purpose

To compare the accuracies of prostate cancer detection and localization between prebiopsy bpMRI and postbiopsy multiparametric MRI (mpMRI) taken on different days, using radical prostatectomy specimens as the reference standards.

Material and methods

Data of 41 total consecutive patients who underwent the following examinations and procedures between September 2015 and March 2017 were collected: (1) magnetic resonance- and/or ultrasonography-guided biopsy after bpMRI; (2) postbiopsy mpMRI; and (3) radical prostatectomy with csPCa. Two radiologists scored suspected lesions on bpMRI and mpMRI independently using Prostate Imaging Reporting and Data System version 2. The diagnostic accuracy of detecting csPCa and the Dice similarity coefficient were obtained. Apparent diffusion coefficient (ADC) ratios were also obtained for quantitative comparison between bpMRI and mpMRI.

Results

Diagnostic accuracies on bpMRI and mpMRI were 0.83 and 0.82 for reader 1; 0.80 and 0.82 for reader 2. There are no significantly different values of diagnostic sensitivities or specificities between the readers or between MRI protocols. Intra-observer Dice similarity coefficient was significantly lower in reader 2, compared to that in reader 1 between the two MRI protocols. The range of mean ADC ratio was 0.281-0.635. There was no statistically significant difference in the ADC ratio between bpMRI and mpMRI.

Conclusions

Diagnostic performance of bpMRI without dynamic contrast enhancement MRI is not significantly different from mpMRI with dynamic contrast enhancement MRI in the detection of csPCa.

Synthetic Apparent Diffusion Coefficient for High b-Value Diffusion-Weighted MRI in Prostate

Purpose

It has been reported that diffusion-weighted imaging (DWI) with ultrahigh b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher Materials and Methods. Fifteen patients (7 malignant and 8 benign) were included in this study retrospectively with the institutional ethical committee approval. All images were acquired at a 3T MR scanner. The ADC values were calculated using a monoexponential model. Synthetic ADC (sADC) for higher b-value increases the diagnostic power of prostate cancer. DWI with higher

Results

No significant difference was observed between actual ADC and sADC for b-value increases the diagnostic power of prostate cancer. DWI with higher p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (p=0.002, paired t-test) in sDWI as compared to DWI. Malignant lesions showed significantly lower sADC as compared to benign lesions (Discussion/

Conclusion

Our initial investigation suggests that the ADC values corresponding to higher b-value can be computed using log-linear relationship derived from lower b-values (b ≤ 1000). Our method might help clinicians to decide the optimal b-value for prostate lesion identification.b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher b-value increases the diagnostic power of prostate cancer. DWI with higher

Correlation between ADC values and Gleason score in evaluation of prostate cancer: multicentre experience and review of the literature

Prostate cancer (PCa) is one of the most common cancers in male population. Multiparametric prostate magnetic resonance imaging (mp-MRI) has assumed a primary role in the diagnosis of PCa, combining morphological and functional data. Among different sequences, functional diffusion weighted imaging (DWI) is a powerful clinical tool which provides information about tissue on a cellular level. However, there is a considerable overlap between either BPH (Benign Prostate Hypertrophy) and prostatic cancer condition, as a different DWI signal intensity could be shown in the normal architecture gland. Apparent diffusion coefficient (ADC) has shown an increasing accuracy in addition to the DWI analysis in detection and localization of PCa. Notably, ADC maps derived DWI sequences has shown an overall high correlation with Gleason score (GS), considering the importance of an accurate grading of focal lesion, as main predictor factor. Furthermore, beyond the comparative analysis with DWI, ADC values has proven to be an useful marker of tumor aggressiveness, providing quantitative information on tumor characteristics according with GS and Gleason pattern, even more strenuous data are needed in order to verify which ADC analysis is more accurate.

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 appearances of primary granulomatous prostatitis

OBJECTIVE

Radiological features of granulomatous prostatitis (GP) overlap with those of prostate adenocarcinoma. Identification of specific GP features may aid diagnosis. We aimed to evaluate the multiparametric MRI (mpMRI) features of GP.

METHODS

We retrospectively reviewed 16 patients from a cohort undergoing mpMRI and transperineal sector-guided prostate biopsies between July 2012 and May 2017. Images were analysed for lesion location, shape, size, extracapsular extension, signal intensity (SI), apparent diffusion coefficient (ADC) values, dynamic contrast enhancement (DCE) pattern and PI-RADS (Prostate Imaging - Reporting and Data System) v2 score.

RESULTS

Histology revealed 13 cases of nonspecific GP and 3 cases of xanthogranulomatous prostatitis. GP lesions were diffuse involving > 50% of the prostate ( n = 13) or nodular ( n = 3). Signal intensity on T ₂ weighted imaging was low and high on diffusion-weighted imaging. ADC values were low (mean 702 ± 79 × 10^-6 mm/s² ). Five patients had DCE imaging with all cases 'positive' as per PI-RADS scoring, with two cases displaying further ring enhancement consistent with abscess formation. Overall PI-RADS score for all cases was 5, indicating high suspicion of prostate cancer.

CONCLUSION

GP is difficult to differentiate from prostate cancer, but typically gives diffuse changes involving > 50% of the gland on mpMRI, with extracapsular extension and rim-enhancing areas. It should be considered a differential diagnosis in patients with recent urinary tract infection (UTI) or prior Bacillus Calmette-Guerin (BCG) treatment.

ADVANCES IN KNOWLEDGE

Prostate MRI imaging features including diffuse changes, extracapsular extension and rim-enhancing areas, in patients with recent UTI or BCG treatment may help identify granulomatous prostatitis cases.

Predictive role of PI-RADSv2 and ADC parameters in differentiating Gleason pattern 3 + 4 and 4 + 3 prostate cancer

PURPOSE

To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard.

METHODS

We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as "low risk," a PI-RADSv2 score ≥ 4 as "high risk" for clinically significant PCa. Mean tumor ADC (ADCT), ADC of adjacent normal tissue (ADCN), and ADCratio (ADCT/ADCN) were calculated. Stepwise regression analysis using tumor location, ADCT and ADCratio, b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3.

RESULTS

119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADCratio was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score ("low" vs. "high") was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADCT (p = 0.03) and ADCratio (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively.

CONCLUSIONS

ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.

Evaluation of ADCratio on liver MRI diffusion to discriminate benign versus malignant solid liver lesions

PURPOSE

The aim of this project is to investigate the usefulness of the absolute liver lesion ADC value and ratio of Apparent diffusion coefficient (ADC) values of a liver lesion and liver parenchyma to discriminate between a benign and malignant lesion.

METHODS

Liver MRI scans performed between January 2009 and June 2015 were retrospectively analysed. Scans were performed on either a 1.5 T or 3 T MRI unit. The type of liver lesion (benign or malignant) was determined by its radiological appearance, histology result and clinical management. Lesions with undetermined diagnosis or MRI studies degraded by artifacts were excluded. Liver cysts were also excluded from the analysis. ADC value of a lesion and liver parenchyma was measured and ADC_ratio was calculated. The values were analysed using independent samples t-test Results:Data set contained 39 benign lesions and 36 malignant lesions. Mean ADC value for benign lesions was 1678, and the mean value for malignant lesions was 1097 with a statistically significant difference of p < 0.001. All lesions with ADC value below 955 were malignant, while all lesions with ADC value above 1880 were benign. ADC value of 1260 was identified as the best available cut-off value for differentiating benign and malignant lesions, achieving sensitivity of 92%, specificity of 80% and an overall accuracy of 89%. The mean lesion to liver ADC_ratio for benign lesions was 1.3467 and for malignant lesions was 0.9038 with a statistically significant difference of p < 0.001. All lesions with ADC_ratio measuring <0.9 were malignant while lesions with ADC_ratio>1.5 were benign. ADC_ratio of 1.1 was identified statistically as the best available cut-off value for differentiating benign from malignant lesions, with sensitivity of 82%, specificity of 86% and an overall accuracy of 92%.

CONCLUSION

Our dataset indicates that lesion to background liver ADC_ratio is superior in discriminating between benign and malignant focal lesions compared to absolute ADC values of the hepatic lesions.

PI-RADS v2 and ADC values: is there room for improvement?

PURPOSE

To determine the diagnostic accuracy of ADC values in combination with PI-RADS v2 for the diagnosis of clinically significant prostate cancer (CS-PCa) compared to PI-RADS v2 alone.

MATERIALS AND METHODS

This retrospective study included 155 men whom underwent 3-Tesla prostate MRI and subsequent MR/US fusion biopsies at a single non-academic center from 11/2014 to 3/2016. All scans were performed with a surface coil and included T2, diffusion-weighted, and dynamic contrast-enhanced sequences. Suspicious findings were classified using Prostate Imaging Reporting and Data System (PI-RADS) v2 and targeted using MR/US fusion biopsies. Mixed-effect logistic regression analyses were used to determine the ability of PIRADS v2 alone and combined with ADC values to predict CS-PCa. As ADC categories are more practical in clinical situations than numeric values, an additional model with ADC categories of ≤ 800 and > 800 was performed.

RESULTS

A total of 243 suspicious lesions were included, 69 of which were CS-PCa, 34 were Gleason score 3+3 PCa, and 140 were negative. The overall PIRADS v2 score, ADC values, and ADC categories are independent statistically significant predictors of CS-PCa (p < 0.001). However, the area under the ROC of PIRADS v2 alone and PIRADS v2 with ADC categories are significantly different in both peripheral and transition zone lesions (p = 0.026 and p = 0.03, respectively) Further analysis of the ROC curves also shows that the main benefit of utilizing ADC values or categories is better discrimination of PI-RADS v2 4 lesions.

CONCLUSION

ADC values and categories help to diagnose CS-PCa when lesions are assigned a PI-RADS v2 score of 4.

Objective value on Apparent diffusion coefficient (ADC) map to categorize the intensity of diffusion-weighted imaging (DWI) restriction for prostate cancer detection on multiparametric prostate MRI

PURPOSE

To identify objective and subjective criteria on multiparametric prostate MRI that can be helpful for prostate cancer detection.

MATERIALS AND METHODS

Retrospective study, IRB approved, including 122 patients who had suspicious lesion on MRI and who underwent prostate biopsy with ultrasonography (US)/MRI imaging fusion. There were 60 patients with positive biopsies and 62 with negative biopsies. MRI of these patients were randomized and evaluated independently by two blinded radiologists. The following variables were analyzed in each lesion: morphology, contours, T2 signal, diffusion restriction (subjective impression and objective values), hyper-enhancement, contact with transition zone or prostatic contour, prostatic contour retraction, Likert and PIRADS classification.

RESULTS

Apparent diffusion coefficient (ADC) value was the best predictor of positivity for prostate cancer, with mean value of 1.08 (SD 0.20) and 1.09 mm2/sec (SD 0.24) on negative biopsies and 0.81 (SD 0.22) and 0.84 mm2/sec (SD 0.22) on positive biopsies for readers 1 and 2, respectively (p < 0.001 in both analysis). For the others categorical variables evaluated the best AUC for reader 1 was subjective intensity of diffusion restriction (AUC of 0.74) and for reader 2 was hyper-enhancement (AUC of 0.65), all inferior comparing to the value of ADC map. Interobserver agreement ranged from 0.13 to 0.75, poor in most measurements, and good or excellent (kappa > 0.6) only in lesion size and ADC values.

CONCLUSIONS

Diffusion restriction with lower ADC-values is the best parameter to predict cancer on MRI prior to biopsy. Efforts to establish an ADC cutoff value would improve cancer detection, especially for less experience reader.

Can Apparent Diffusion Coefficient Values Assist PI-RADS Version 2 DWI Scoring? A Correlation Study Using the PI-RADSv2 and International Society of Urological Pathology Systems

OBJECTIVE

The purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines.

MATERIALS AND METHODS

In this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone.

RESULTS

ADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader.

CONCLUSION

ADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.

Quantitative evaluation of the relative apparent diffusion coefficient values on multiparametric magnetic resonance imaging to predict higher Gleason score prostate cancer

INTRODUCTION

Apparent diffusion coefficient (ADC) values on multiparametric magnetic resonance imaging (mpMRI) have been reported to correlate with high-Gleason score (GS) prostate cancer. However, the relative ADC values between tumor lesions and normal tissue have been suggested as more suitable than the absolute ADC values for evaluation of diffusion abnormalities, because absolute ADC values are susceptible to differences in scanners or scanner settings. The present study evaluated the usefulness of the relative assessment of ADC values between tumor lesions and normal tissue on preoperative mpMRI for the prediction of high-risk prostate cancer on radical prostatectomy specimens.

MATERIALS AND METHODS

A retrospective analysis of 48 men who underwent radical prostatectomy between January 2013 and December 2014 was conducted. MpMRI was performed with a 3.0-T scanner using b-values of 0 and 1500 s/mm². ADC values of the tumor (ADC_TUMOR) and normal prostate and the relative ADC tumor/normal ratio (ADC_TNR) were evaluated by two radiologists.

RESULTS

The inter-rater reliability between two radiologists for ADC_TUMOR measurement was high, with Pearson's r = 0.982. There was no difference in ADC_TUMOR between GS ≤7 and GS ≥8. In contrast, ADC_TNR was significantly lower in GS ≥8 than in GS ≤7. ROC curves of ADC_TNR to predict higher GS (≥8) showed better classification performance (AUC = 0.8243, p = .0012 by radiologist A and AUC = 0.7961, p = .0031 by radiologist B) than of ADC_TUMOR.

CONCLUSIONS

The relative assessment of ADC values between tumor lesions and normal tissue could improve the detection rate of high-risk prostate cancers.

Utility of quantitative apparent diffusion coefficient measurements and normalized apparent diffusion coefficient ratios in the diagnosis of clinically significant peripheral zone prostate cancer

OBJECTIVE

The aim of this study is to evaluate the utility of quantitative apparent diffusion coefficient (ADC) measurements and normalized ADC ratios in multiparametric MRI for the diagnosis of clinically significant peripheral zone (PZ) prostate cancer particularly among equivocally suspicious prostate lesions.

METHODS

A retrospective analysis of 95 patients with PZ lesions by PI-RADSv2 criteria, and who underwent subsequent MRI-US fusion biopsy, was approved by an institutional review board. Two radiologists independently measured ADC values in regions of interest (ROIs) of PZ lesions and calculated normalized ADC ratio based on ROIs in the bladder lumen. Diagnostic performance was evaluated using ROC. Inter observer variability was assessed using intraclass correlation coefficient (ICC).

RESULTS

Mean ADC and normalized ADC ratios for clinically significant and non-clinically significant lesions were 0.763 × 10-3 mm² s^-1, 29.8%; and 1.135 × 10-3 mm² s^-1, 47.2% (p < 0.001), respectively. Area under the ROC curve (AUC) was 0.880 [95% CI (0.816-0.944) and 0.885 (95% CI (0.814-0.955)] for ADC and ADC ratio, respectively. Optimal AUC threshold for ADC was 0.843 × 10-3 mm² s^-1 (Sn 70.5%, Sp 88.2%) and for normalized ADC was 33.1% (Sn 75.0%, Sp 95.7%). intraclass correlation coefficient was high at 0.889.

CONCLUSION

Quantitative ADC measurement in PZ prostate lesions demonstrates excellent diagnostic performance in differentiating clinically significant from non-clinically significant prostate cancer with high inter observer correlation. Advances In knowledge: Quantitative ADC is presented as an additional method to evaluate lesions in mpMRI of the prostate. This technique may be incorporated in new and existing methods to improve detection and discrimination of clinically significant prostate cancer.

Comparison of quantitative apparent diffusion coefficient parameters with prostate imaging reporting and data system V2 assessment for detection of clinically significant peripheral zone prostate cancer

PURPOSE

To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2.

METHODS

We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean ADC_T, mean ADC_N, ADC_ratio (ADC_T/ADC_N) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC).

RESULTS

Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) ADC_T (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) ADC_T (0.86) was higher than ADC_ratio (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than ADC_ratio (0.56, p = 0.02). ADC_T performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). ADC_ratio performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition.

CONCLUSIONS

When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with ADC_T providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than ADC_ratio. csPC definition did not affect PI-RADSv2 diagnostic performance.

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

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

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

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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.

New prostate cancer prognostic grade group (PGG): Can multiparametric MRI (mpMRI) accurately separate patients with low-, intermediate-, and high-grade cancer?

PURPOSE

Our objective is to determine the accuracy of multiparametric MRI (mpMRI) in predicting pathologic grade of prostate cancer (PCa) after radical prostatectomy (RP) using simple apparent diffusion coefficient metrics and, specifically, whether mpMRI can accurately separate disease into one of two risk categories (low vs. higher grade) or one of three risk categories (low, intermediate, or high grade) corresponding to the new prognostic grade group (PGG) criteria.

METHODS

This retrospective, HIPAA-compliant, IRB-approved study included 140 patients with PCa who underwent 3 T mpMRI with endorectal coil and transrectal ultrasound-guided (TRUS-G) biopsy before RP. MpMRI was used to classify lesions using a two-tier (low-grade/PGG 1 vs. high-grade/PGG 2-5) or a three-tier system (low-grade/PGG 1 vs. intermediate-grade/PGG 2 vs. high-grade/PGG 3-5). Accuracy of mpMRI was compared against RP for each system.

RESULTS

The predictive accuracy of mpMRI using the two-tier system is higher than when using three-tier system (0.77 and 0.45, respectively). There were similar rates of undergrading between mpMRI and TRUS-G biopsy compared to RP (16% & 21%; respectively); rate of overgrading was higher for mpMRI vs. TRUS-G biopsy compared to RP (42% & 17%, respectively). When mpMRI and TRUS-G biopsy are combined, rate of undergrading is 1.4% and overgrading is 11%.

CONCLUSIONS

MpMRI predictive accuracy is higher when using a two-tier vs. a three-tier system, suggesting that advanced metrics may be necessary to delineate intermediate- from high-grade disease. Rates of under- and overgrading decreased when mpMRI and TRUS-G biopsy are combined, suggesting that these techniques may be complementary in predicting tumor grade.

Diffusion weighted imaging of the prostate-principles, application, and advances

This review article aims to provide an overview on the principles of diffusion-weighted magnetic resonance imaging (DW-MRI) and its applications in the imaging of the prostate. DW-MRI with regards to different applications for prostate cancer (PCa) detection and characterization, local staging as well as for active surveillance (AS) and tumor recurrence after radical prostatectomy (RP) will be discussed. Furthermore, advances in DW-MRI techniques like diffusion kurtosis imaging (DKI) will be presented.

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

PURPOSE

To assess the impact of patient race and age on the performance of apparent diffusion coefficient (ADC) values for assessment of prostate cancer aggressiveness.

MATERIALS AND METHODS

457 prostate cancer patients who underwent 3T phased-array coil prostate MRI including diffusion-weighted imaging (DWI; maximal b-value 1000 s/mm²) before prostatectomy were included. Mean ADC of a single dominant lesion was measured in each patient, using histopathologic findings from the prostatectomy specimen as reference. In subsets defined by race and age, ADC values were compared between Gleason score (GS) ≤ 3 + 4 and GS ≥ 4 + 3 tumors.

RESULTS

81% of patients were Caucasian, 12% African-American, 7% Asian-American. 13% were <55 years, 42% 55-64 years, 41% 65-74 years, and 4% ≥75 years. 63% were GS ≤ 3 + 4, 37% GS ≥ 4 + 3. ADC was significantly lower in GS ≥ 4 + 3 tumors than in GS ≤ 3 + 4 tumors in the entire cohort, as well as in Caucasian, African-American, and all four age groups (P ≤ 0.015). AUC for differentiation of GS ≤ 3 + 4 and GS ≥ 4 + 3 as well as optimal ADC threshold was Caucasian: 0.73/≤848; African-American: 0.76/≤780; Asian-American: 0.66/≤839: <55 years, 0.73/≤830; 55-64 years, 0.71/≤800; 65-74 years, 0.74/≤872; ≥75 years, 0.79/≤880. A race-optimized ADC threshold resulted in higher specificity in African-American than Caucasian men (84.9% vs. 67.1%, P = 0.045); age-optimized ADC threshold resulted in higher sensitivity in patients aged ≥75 years than <55 years or 55-64 years (100.0% vs. 53.6%-73.3%; P < 0.001).

CONCLUSION

Patients' race and age may impact the diagnostic performance and optimal threshold when applying ADC values for evaluation of prostate cancer aggressiveness.

The utility of quantitative ADC values for differentiating high-risk from low-risk prostate cancer: a systematic review and meta-analysis

PURPOSE

The purpose of the study is to perform a meta-analysis of studies investigating the diagnostic performance of apparent diffusion coefficient (ADC) values in separating high-risk from low-risk prostate cancer (PCa).

METHODS

MEDLINE and EMBASE databases were searched in December 2015 for studies reporting diagnostic performance of ADC values for discriminating high-risk from low-risk PCa and providing sufficient data to construct 2 × 2 contingency tables. Diagnostic performance was quantitatively pooled using a bivariate random-effects model including subgroup analysis and assessment of study heterogeneity and methodological quality.

RESULTS

13 studies were included, providing 1107 tumor foci in 705 patients. Heterogeneity among studies was moderate (τ² = 0.222). Overall sensitivity was 76.9% (95% CI 68.6-83.6%); overall specificity was 77.0% (95% CI 69.9-82.8%); and summary AUC was 0.67. Inverse correlation between sensitivity and specificity (ρ = -0.58) indicated interstudy heterogeneity was partly due to variation in threshold for test positivity. Primary biases were readers' knowledge of Gleason score during ADC measurement, lack of prespecified ADC thresholds, and lack of prostatectomy as reference in some studies. Higher sensitivity was seen in studies published within the past 2 years and studies not using b value of at least 2000; higher specificity was associated with involvement of one, rather than two, readers measuring ADC. Field strength, coil selection, and advanced diffusion metrics did not significantly impact diagnostic performance.

CONCLUSION

ADC values show moderate accuracy in separating high-risk from low-risk PCa, although important biases may overestimate performance and unexplained sources of heterogeneity likely exist. Further studies using a standardized methodology and addressing identified weaknesses may help guide the use of ADC values for clinical decision-making.

Apparent diffusion coefficient normalization of normal liver: Will it improve the reproducibility of diffusion-weighted imaging at different MR scanners as a new biomarker?

Apparent diffusion coefficient (ADC) measurement in diffusion-weighted imaging (DWI) has been reported to be a helpful biomarker for detection and characterization of lesion. In view of the importance of ADC measurement reproducibility, the aim of this study was to probe the variability of the healthy hepatic ADC values measured at 3 MR scanners from different vendors and with different field strengths, and to investigate the reproducibility of normalized ADC (nADC) value with the spleen as the reference organ. Thirty enrolled healthy volunteers received DWI with GE 1.5T, Siemens 1.5T, and Philips 3.0T magnetic resonance (MR) systems on liver and spleen (session 1) and were imaged again after 10 to 14 days using only GE 1.5T MR and Philips 3.0T MR systems (session 2). Interscan agreement and reproducibility of ADC measurements of liver and the calculated nADC values (ADCliver/ADCspleen) were statistically evaluated between 2 sessions. In session 1, ADC and nADC values of liver were evaluated for the scanner-related variability by 2-way analysis of variance and intraclass correlation coefficients (ICCs). Coefficients of variation (CVs) of ADCs and nADCs of liver were calculated for both 1.5 and 3.0-T MR system. Interscan agreement and reproducibility of ADC measurements of liver and related nADCs between 2 sessions were found to be satisfactory with ICC values of 0.773 to 0.905. In session 1, the liver nADCs obtained from different scanners were consistent (P = 0.112) without any significant difference in multiple comparison (P = 0.117 to >0.99) by using 2-way analysis of variance with post-hoc analysis of Bonferroni method, although the liver ADCs varied significantly (P < 0.001). nADCs measured by 3 scanners were in good interscanner agreements with ICCs of 0.685 to 0.776. The mean CV of nADCs of both 1.5T MR scanners (9.6%) was similar to that of 3.0T MR scanner (8.9%). ADCs measured at 3 MR scanners with different field strengths and vendors could not be compared directly. Normalization of ADCs, however, may provide better reproducibility by overcoming these potential issues.

Diffusion-Weighted Genitourinary Imaging

This review article aims to provide an overview on of diffusion-weighted MR imaging (DW-MR imaging) in the urogenital tract. Compared with conventional cross-sectional imaging methods, the additional value of DW-MR imaging in the detection and further characterization of benign and malignant lesions of the kidneys, bladder, prostate, and pelvic lymph nodes is discussed as well as the role of DW-MR imaging in the evaluation of treatment response.

Prostate MR Imaging: An Update

Improvements in prostate MR imaging techniques and the introduction of MR imaging-targeted biopsies have had central roles in prostate cancer (PCa) management. The role of MR imaging has progressed from largely staging patients with biopsy-proven PCa to detecting, characterizing, and guiding the biopsy of suspected PCa. These diagnostic advances, combined with improved therapeutic interventions, have led to a more sophisticated and individually tailored approach to patients' unique PCa profile. This review discusses the MR imaging, a standardized reporting scheme, and the role of fusion-targeted prostate biopsy.

Comparison of PI-RADS 2, ADC histogram-derived parameters, and their combination for the diagnosis of peripheral zone prostate cancer

PURPOSE

The purpose of this study was to compare the PI-RADS V2 scores, ADC histogram-derived parameters, and their combination for the diagnosis of clinically significant peripheral zone prostate cancer (PCa).

MATERIALS AND METHODS

The IRB approved this retrospective study of 47 men who underwent 1.5 Tesla endorectal prostate magnetic resonance imaging (MRI). Informed consent was waived. Two readers identified and scored MRI lesions using PI-RADS V2. Their mean, median, 10th, 25th, 75th percentile ADC values, and normalized ratio were also calculated. Multilevel logistic regression and receiver-operating characteristic (ROC) curve analyses assessed their diagnostic performance. Clinically significant PCa was defined as tumor volume over 0.5 cc and Gleason grade of 4 or 5 on prostatectomy.

RESULTS

The area under the ROC curve (A _z) of the overall and diffusion-weighted imaging (DWI) PI-RADS V2 scores were 0.69 and 0.84 (reader-1), and 0.68 and 0.73 (reader-2). The A _z of ADC parameters ranged from 0.68 to 0.75 for both readers. Compared to other predictors, DWI PI-RADS V2 yielded the highest A _z for identification of significant cancer; but, except for reader-1 75th percentile ADC, the differences were not statistically significant (P > 0.05). Adding ADC parameters to PI-RADS V2 scores did not improve their diagnostic ability.

CONCLUSION

DWI PI-RADS V2 score may a better predictor of clinically significant PCa than the overall PI-RADS V2 score, but its diagnostic performance was not significantly improved by the addition of objective ADC value measurements.

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.

Multiparametric MRI of the prostate: diagnostic performance and interreader agreement of two scoring systems

OBJECTIVE

To compare the diagnostic accuracies and interreader agreements of the Prostate Imaging Reporting and Data System (PI-RADS) v. 2 and University of California San Francisco (UCSF) multiparametric prostate MRI scale for diagnosing clinically significant prostate cancer.

METHODS

This institutional review board-approved retrospective study included 49 males who had 1.5 T endorectal MRI and prostatectomy. Two radiologists scored suspicious lesions on MRI using PI-RADS v. 2 and the UCSF scale. Percent agreement, 2 × 2 tables and the area under the receiver operating characteristic curves (Az) were used to assess and compare the individual and overall scores of these scales. Interreader agreements were estimated with kappa statistics.

RESULTS

Reader 1 (R1) detected 78 lesions, and Reader 2 (R2) detected 80 lesions. Both identified 52 of 65 significant cancers. The Az for PI-RADS v. 2 and UCSF scale for R1 were 0.68 and 0.69 [T2 weighted imaging (T2WI)], 0.75 and 0.68 [diffusion-weighted imaging (DWI)] and 0.64 and 0.72 (overall score), respectively, and were 0.72 and 0.75 (T2WI), 0.73 and 0.67 (DWI) and 0.66 and 0.75 (overall score) for R2. The dynamic contrast-enhanced percent agreements between scales were 100% (R1) and 95% (R2). PI-RADS v. 2 DWI of R1 performed better than UCSF DWI (Az = 0.75 vs Az = 0.68; p = 0.05); no other differences were found. The interreader agreements were higher for PI-RADS v. 2 (T2WI: 0.56 vs 0.42; DWI: 0.60 vs 0.46; overall: 0.61 vs 0.42). The UCSF approach to derive the overall PI-RADS v. 2 scores increased the Az for the identification of significant cancer (R1 to 0.76, p < 0.05; R2 to 0.71, p = 0.35).

CONCLUSION

Although PI-RADS v. 2 DWI score may have a higher discriminatory performance than the UCSF scale counterpart to diagnose clinically significant cancer, the utilization of the UCSF scale weighing system for the integration of PI-RADS v. 2 individual parameter scores improved the accuracy its overall score.

ADVANCES IN KNOWLEDGE

PI-RADS v. 2 is moderately accurate for the identification of clinically significant prostate cancer, but the utilization of alternative approaches to derive the overall PI-RADS v. 2 score, including the one used by the UCSF system, may improve its diagnostic accuracy.

Ratio of Tumor to Normal Prostate Tissue Apparent Diffusion Coefficient as a Method for Quantifying DWI of the Prostate

OBJECTIVE

The purpose of this study was to investigate the ability of the apparent diffusion coefficient (ADC) ratio of tumor to normal prostate tissue to overcome inherent variability based on choice of b values, with whole-mount histopathologic analysis as the reference standard for tumor identification.

MATERIALS AND METHODS

Thirty-nine patients with prostate cancer underwent 3-T MRI, including DWI with b values of 0, 150, 750, and 1000 s/mm(2). ADC maps were derived from four b value combinations. Histologically derived ROIs were defined for prostate tumor and benign prostate tissue to generate a ratio. The concordance correlation coefficient was used to evaluate agreement and reproducibility at different b values. Bland-Altman plots were used to evaluate the pattern of relative measurement difference between b value combinations. The relationship between ADC values and Gleason score was tested by Spearman rank correlation.

RESULTS

ADC values varied depending on the b value combination selected. The concordance correlation coefficient was higher for ADC ratios (0.883; 95% CI, 0.816-0.927) compared with absolute ADC values for normal tissue (0.873; 95% CI, 0.799-0.921) and tumor (0.792; 95% CI, 0.688-0.864). The ADC ratio concordance correlation coefficient for transition zone tumors was considerably higher than that for the peripheral zone in all cases. Bland-Altman analysis showed higher variation for ADC maps incorporating a b value of zero for both ratio and absolute values. There was a stronger inverse relationship to Gleason score for ADC ratios (rho, -0.354 to -0.456) compared with absolute ADC values (rho, -0.117 to -0.379).

CONCLUSION

The use of a simple ratio of prostate tumor ADC to normal tissue ADC improved the concordance between different b value combinations and could provide a more robust means of assessing restricted diffusion in the prostate.

Does normalisation improve the diagnostic performance of apparent diffusion coefficient values for prostate cancer assessment? A blinded independent-observer evaluation

AIM

To evaluate the performance of normalised apparent diffusion coefficient (ADC) values for prostate cancer assessment when performed by independent observers blinded to histopathology findings.

MATERIALS AND METHODS

Fifty-eight patients undergoing 3 T phased-array coil magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI; maximal b-value 1000 s/mm(2)) before prostatectomy were included. Two radiologists independently evaluated the images, unaware of the histopathology findings. Regions of interest (ROIs) were drawn within areas showing visually low ADC within the peripheral zone (PZ) and transition zone (TZ) bilaterally. ROIs were also placed within regions in both lobes not suspicious for tumour, allowing computation of normalised ADC (nADC) ratios between suspicious and non-suspicious regions. The diagnostic performance of ADC and nADC were compared.

RESULTS

For PZ tumour detection, ADC achieved significantly higher area under the receiver operating characteristic curve (AUC; p=0.026) and specificity (p=0.021) than nADC for reader 1, and significantly higher AUC (p=0.025) than nADC for reader 2. For TZ tumour detection, nADC achieved significantly higher specificity (p=0.003) and accuracy (p=0.004) than ADC for reader 2. For PZ Gleason score >3+3 tumour detection, ADC achieved significantly higher AUC (p=0.003) and specificity (p=0.005) than nADC for reader 1, and significantly higher AUC (p=0.023) than nADC for reader 2. For TZ Gleason score >3+3 tumour detection, ADC achieved significantly higher specificity (p=0.019) than nADC for reader 1.

CONCLUSION

In contrast to prior studies performing unblinded evaluations, ADC was observed to outperform nADC overall for two independent observers blinded to the histopathology findings. Therefore, although strategies to improve the utility of ADC measurements in prostate cancer assessment merit continued investigation, caution is warranted when applying normalisation to improve diagnostic performance in clinical practice.

A literature review of the association between diffusion-weighted MRI derived apparent diffusion coefficient and tumour aggressiveness in pelvic cancer

Diffusion-weighted magnetic resonance imaging (DW-MRI) is used extensively to improve tumour detection and localization because it offers excellent soft tissue contrast between malignant and non-malignant tissues. It also provides a quantitative biomarker; the apparent diffusion coefficient (ADC) can be derived from DW-MRI sequences using multiple diffusion weightings. ADC reflects the tumour microenvironment, e.g. cell membrane integrity and cellularity and has potential for reporting on tumour aggressiveness. This review focuses on the use of the DW-MRI derived imaging biomarker ADC to reflect tumour aggressiveness and its potential impact in managing pelvic cancer patients. The clinical studies which evaluate the role of ADC in pelvic tumours (prostate, bladder, rectal, ovary, cervix and uterus) are summarized and the evidence linking ADC values with tumour aggressiveness is evaluated.

Apparent diffusion coefficient ratio correlates significantly with prostate cancer gleason score at final pathology

PURPOSE

To evaluate the correlation between apparent diffusion coefficient measurements (ADCtumor and ADCratio ) and the Gleason score from radical prostatectomy specimens.

MATERIALS AND METHODS

Seventy-one patients with clinically localized prostate cancer scheduled for radical prostatectomy were prospectively enrolled. Multiparametric magnetic resonance imaging (MRI) was performed prior to prostatectomy and mean ADC values from both cancerous (ADCtumor ) and benign (ADCbenign ) tissue were measured to calculate the ADCratio (ADCtumor divided by ADCbenign ). The ADC measurements were correlated with the Gleason score from the prostatectomy specimens.

RESULTS

The association between ADC measurements and Gleason score showed a significant negative correlation (P < 0.001) with Spearman's rho for ADCtumor (-0.421) and ADCratio (-0.649). There was a statistically significant difference between ADC measurements and the Gleason score for all tumors (P = 0.001). Receiver operating characteristic curve analysis showed an overall area under the curve (AUC) of 0.73 (ADCtumor ) to 0.80 (ADCratio ) in discriminating Gleason score 6 from Gleason score ≥7 tumors. The AUC changed to 0.72 (ADCtumor ) and 0.90 (ADCratio ) when discriminating Gleason score ≤7(3+4) from Gleason score ≥7(4+3).

CONCLUSION

ADC measurements showed a significant correlation with tumor Gleason score at final pathology. The ADCratio demonstrated the best correlation compared to the ADCtumor value and radically improved accuracy in discriminating Gleason score ≤7(3+4) from Gleason score ≥7(4+3) tumors.