Evaluation of semi-quantitative dynamic contrast-enhanced MRI parameters for prostate cancer in correlation to whole-mount histopathology

Is There an Added Value of Quantitative DCE-MRI by Magnetic Resonance Dispersion Imaging for Prostate Cancer Diagnosis?

In this multicenter, retrospective study, we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients, including 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast-enhanced MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists was evaluated using Cohen's Kappa. On a per-patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI was 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2), these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI, and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen's Kappa = 0.4250, p = 0.004). The results of this study show the potential of MRDI to improve inter-observer variability and the detection of csPCa.

Full resolution reconstruction of whole-mount sections from digitized individual tissue fragments

Whole-mount sectioning is a technique in histopathology where a full slice of tissue, such as a transversal cross-section of a prostate specimen, is prepared on a large microscope slide without further sectioning into smaller fragments. Although this technique can offer improved correlation with pre-operative imaging and is paramount for multimodal research, it is not commonly employed due to its technical difficulty, associated cost and cumbersome integration in (digital) pathology workflows. In this work, we present a computational tool named PythoStitcher which reconstructs artificial whole-mount sections from digitized tissue fragments, thereby bringing the benefits of whole-mount sections to pathology labs currently unable to employ this technique. Our proposed algorithm consists of a multi-step approach where it (i) automatically determines how fragments need to be reassembled, (ii) iteratively optimizes the stitch using a genetic algorithm and (iii) efficiently reconstructs the final artificial whole-mount section on full resolution (0.25 µm/pixel). PythoStitcher was validated on a total of 198 cases spanning five datasets with a varying number of tissue fragments originating from different organs from multiple centers. PythoStitcher successfully reconstructed the whole-mount section in 86-100% of cases for a given dataset with a residual registration mismatch of 0.65-2.76 mm on automatically selected landmarks. It is expected that our algorithm can aid pathology labs unable to employ whole-mount sectioning through faster clinical case evaluation and improved radiology-pathology correlation workflows.

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Characterization of high-grade prostate cancer at multiparametric MRI using a radiomic-based computer-aided diagnosis system as standalone and second reader

PURPOSE

The purpose of this study was to develop and test across various scanners a zone-specific region-of-interest (ROI)-based computer-aided diagnosis system (CAD) aimed at characterizing, on MRI, International Society of Urological Pathology (ISUP) grade≥2 prostate cancers.

MATERIALS AND METHODS

ROI-based quantitative models were selected in multi-vendor training (265 pre-prostatectomy MRIs) and pre-test (112 pre-biopsy MRIs) datasets. The best peripheral and transition zone models were combined and retrospectively assessed in internal (158 pre-biopsy MRIs) and external (104 pre-biopsy MRIs) test datasets. Two radiologists (R1/R2) retrospectively delineated the lesions targeted at biopsy in test datasets. The CAD area under the receiver operating characteristic curve (AUC) for characterizing ISUP≥2 cancers was compared to that of the Prostate Imaging-Reporting and Data System version2 (PI-RADSv2) score prospectively assigned to targeted lesions.

RESULTS

The best models used the 25th apparent diffusion coefficient (ADC) percentile in transition zone and the 2nd ADC percentile and normalized wash-in rate in peripheral zone. The PI-RADSv2 AUCs were 82% (95% confidence interval [CI]: 74-87) and 86% (95% CI: 81-91) in the internal and external test datasets respectively. They were not different from the CAD AUCs obtained with R1 and R2 delineations, in the internal (82% [95% CI: 76-89], P = 0.95 and 85% [95% CI: 78-91], P = 0.55) and external (82% [95% CI: 74-91], P = 0.41 and 86% [95% CI:78-95], P = 0.98) test datasets. The CAD yielded sensitivities of 86-89% and 90-91%, and specificities of 64-65% and 69-75% in the internal and external test datasets respectively.

CONCLUSION

The CAD performance for characterizing ISUP grade≥2 prostate cancers on MRI is not different from that of PI-RADSv2 score across two test datasets.

Optimal length and temporal resolution of dynamic contrast-enhanced MR imaging for the differentiation between prostate cancer and normal peripheral zone tissue

The value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the detection of prostate cancer is controversial. There are currently insufficient peer reviewed published data or expert consensus to support routine adoption of DCE-MRI for clinical use. Thus, the objective of this study was to explore the optimal temporal resolution and measurement length for DCE-MRI to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate by non-parametric MRI analysis and to compare with a quantitative MRI analysis. Predictors of interest were onset time, relative signal intensity (RSI), wash-in slope, peak enhancement, wash-out and wash-out slope determined from non-parametric characterisation of DCE-MRI intensity-time profiles. The discriminatory power was estimated from C-statistics based on cross validation. We analyzed 54 patients with 97 prostate tissue specimens (47 prostate cancer, 50 normal prostate tissue) of the peripheral zone, mean age 63.8 years, mean prostate-specific antigen 18.9 ng/mL and mean of 10.5 days between MRI and total prostatectomy. When comparing prostate cancer tissue with normal prostate tissue, median RSI was 422% vs 330%, and wash-in slope 0.870 vs 0.539. The peak enhancement of 67 vs 42 was higher with prostate cancer tissue, while wash-out (-30% vs -23%) and wash-out slope (-0.037 vs -0.029) were lower, and the onset time (32 seconds) was comparable. The optimal C-statistics was 0.743 for temporal resolution of 8.0 seconds and measurement length of 2.5 minutes compared with 0.656 derived from a quantitative MRI analysis. This study provides evidence that the use of a non-parametric approach instead of a more established parametric approach resulted in greater precision to differentiate cancerous from normal prostate tissue of the peripheral zone of the prostate.

Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy

BACKGROUND

Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level.

METHODS

Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov-Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen's d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone.

RESULTS

All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours.

CONCLUSIONS

Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning.

Revisiting DCE-MRI: Classification of Prostate Tissue Using Descriptive Signal Enhancement Features Derived From DCE-MRI Acquisition With High Spatiotemporal Resolution

METHODS

A retrospective study (from January 2016 to July 2019) including 75 subjects (mean, 65 years; 46-80 years) with 2.5-second temporal resolution DCE-MRI and PIRADS 4 or 5 lesions was performed. Fifty-four subjects had biopsy-proven prostate cancer (Gleason 6, 15; Gleason 7, 20; Gleason 8, 13; Gleason 9, 6), whereas 21 subjects had negative MRI/ultrasound fusion-guided biopsies. Voxel-wise analysis of contrast signal enhancement was performed for all time points using custom-developed software, including automatic arterial input function detection. Seven descriptive parameter maps were calculated: normalized maximum signal intensity, time to start, time to maximum, time-to-maximum slope, and maximum slope with normalization on maximum signal and the arterial input function (SMN1, SMN2). The parameters were compared with ADC using multiparametric machine-learning models to determine classification accuracy. A Wilcoxon test was used for the hypothesis test and the Spearman coefficient for correlation.

RESULTS

There were significant differences (P < 0.05) for all 7 DCE-derived parameters between the normal peripheral zone versus PIRADS 4 or 5 lesions and the biopsy-positive versus biopsy-negative lesions. Multiparametric analysis showed better performance when combining ADC + DCE as input (accuracy/sensitivity/specificity, 97%/93%/100%) relative to ADC alone (accuracy/sensitivity/specificity, 94%/95%/95%) and to DCE alone (accuracy/sensitivity/specificity, 78%/79%/77%) in differentiating the normal peripheral zone from PIRADS lesions, biopsy-positive versus biopsy-negative lesions (accuracy/sensitivity/specificity, 68%/33%/81%), and Gleason 6 versus ≥7 prostate cancer (accuracy/sensitivity/specificity, 69%/60%/72%).

CONCLUSIONS

Descriptive perfusion characteristics derived from high-resolution DCE-MRI using model-free computations show significant differences between normal and cancerous tissue but do not reach the accuracy achieved with solely ADC-based classification. Combining ADC with DCE-based input features improved classification accuracy for PIRADS lesions, discrimination of biopsy-positive versus biopsy-negative lesions, and differentiation between Gleason 6 versus Gleason ≥7 lesions.

Dynamic contrast-enhanced (DCE) MR imaging: the role of qualitative and quantitative parameters for evaluating prostate tumors stratified by Gleason score and PI-RADS v2

PURPOSE

To investigate the role of qualitative and quantitative DCE-MRI parameters in prostate cancer (PCa) stratified by whole-mount histopathology (WMHP) Gleason score (GS) and PI-RADSv2.

METHODS

This retrospective study included 323 PCa tumors in 254 men, who underwent 3T MRI prior to prostatectomy, 7/2009-12/2016. Qualitative DCE curve types included type 1 (progressive), type 2 (plateau) and type 3 (washout). Quantitative DCE-MRI pharmacokinetic (PK) parameters included K^trans (influx volume transfer coefficient), K_ep (efflux reflux rate constant) and iAUC (initial area under the curve). DCE-MRI features of true positive lesions were evaluated for overall, index, transition zone (TZ) and peripheral zone (PZ), based on GS grade (low = 6, high > 6) and PI-RADSv2 score using SPSSv24.

RESULTS

There were 57 (17.6%) low-grade and 266 (82.4%) high-grade PCa lesions. PI-RADSv2 3, 4 and 5 included 106, 120 and 97 lesions, respectively. 251 (77.7%) and 72 (22.3%) lesions were located in PZ and TZ, respectively. High-grade lesions had significantly higher proportion of Type 3 curves compared to low-grade lesions in overall (70.3% vs. 54.4%) and TZ (73.5% vs. 43.5%). As PI-RADSv2 increased, the proportion of type 3 curve significantly increased for overall (80.4-51.9%), index (80.4-54.7%) and PZ (78.7-52.1%) lesions. Among PK parameters, K^trans (0.43 vs 0.32) and iAUC (8.99 vs 6.9) for overall PCa, K^trans (0.43 vs 0.31) and iAUC (9 vs 6.67) for PZ PCa, and iAUC (8.94 vs 7.42) for index PCa were significantly higher for high-grade versus low-grade lesions. Also, K^trans (0.51-0.34), K_ep (1.75-1.29) and iAUC (9.79-7.6) for overall PCa, K^trans (0.53-0.32), K_ep (1.81-1.26) and iAUC (9.83-7.34) for PZ PCa; and K_ep (1.79-1.17) and iAUC (11.3-8.45) for index PCa increased significantly with a higher PI-RADSv2 score.

CONCLUSIONS

The results of study show the possible utility of qualitative and quantitative DCE-MRI parameters for assessment of PCa GS and PI-RADSv2 categorization.

Evaluation of T1 relaxation time in prostate cancer and benign prostate tissue using a Modified Look-Locker inversion recovery sequence

Purpose of this study was to evaluate the diagnostic performance of T1 relaxation time (T1) for differentiating prostate cancer (PCa) from benign tissue as well as high- from low-grade PCa. Twenty-three patients with suspicion for PCa were included in this prospective study. 3 T MRI including a Modified Look-Locker inversion recovery sequence was acquired. Subsequent targeted and systematic prostate biopsy served as a reference standard. T1 and apparent diffusion coefficient (ADC) value in PCa and reference regions without malignancy as well as high- and low-grade PCa were compared using the Mann-Whitney U test. The performance of T1, ADC value, and a combination of both to differentiate PCa and reference regions was assessed by receiver operating characteristic (ROC) analysis. T1 and ADC value were lower in PCa compared to reference regions in the peripheral and transition zone (p < 0.001). ROC analysis revealed high AUCs for T1 (0.92; 95%-CI, 0.87-0.98) and ADC value (0.97; 95%-CI, 0.94 to 1.0) when differentiating PCa and reference regions. A combination of T1 and ADC value yielded an even higher AUC. The difference was statistically significant comparing it to the AUC for ADC value alone (p = 0.02). No significant differences were found between high- and low-grade PCa for T1 (p = 0.31) and ADC value (p = 0.8). T1 relaxation time differs significantly between PCa and benign prostate tissue with lower T1 in PCa. It could represent an imaging biomarker for PCa.

Preclinical Molecular Imaging for Precision Medicine in Breast Cancer Mouse Models

Precision and personalized medicine is gaining importance in modern clinical medicine, as it aims to improve diagnostic precision and to reduce consequent therapeutic failures. In this regard, prior to use in human trials, animal models can help evaluate novel imaging approaches and therapeutic strategies and can help discover new biomarkers. Breast cancer is the most common malignancy in women worldwide, accounting for 25% of cases of all cancers and is responsible for approximately 500,000 deaths per year. Thus, it is important to identify accurate biomarkers for precise stratification of affected patients and for early detection of responsiveness to the selected therapeutic protocol. This review aims to summarize the latest advancements in preclinical molecular imaging in breast cancer mouse models. Positron emission tomography (PET) imaging remains one of the most common preclinical techniques used to evaluate biomarker expression in vivo, whereas magnetic resonance imaging (MRI), particularly diffusion-weighted (DW) sequences, has been demonstrated as capable of distinguishing responders from nonresponders for both conventional and innovative chemo- and immune-therapies with high sensitivity and in a noninvasive manner. The ability to customize therapies is desirable, as this will enable early detection of diseases and tailoring of treatments to individual patient profiles. Animal models remain irreplaceable in the effort to understand the molecular mechanisms and patterns of oncologic diseases.

Automatic stratification of prostate tumour aggressiveness using multiparametric MRI: a horizontal comparison of texture features

Background: Previous studies have identified apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) can stratify prostate cancer into high- and low-grade disease (HG and LG, respectively). In this study, we consider the improvement of incorporating texture features (TFs) from T2-weighted (T2w) multiparametric magnetic resonance imaging (mpMRI) relative to mpMRI alone to predict HG and LG disease. Material and methods: In vivo mpMRI was acquired from 30 patients prior to radical prostatectomy. Sequences included T2w imaging, DWI and dynamic contrast enhanced (DCE) MRI. In vivo mpMRI data were co-registered with 'ground truth' histology. Tumours were delineated on the histology with Gleason scores (GSs) and classed as HG if GS ≥ 4 + 3, or LG if GS ≤ 3 + 4. Texture features based on three statistical families, namely the grey-level co-occurrence matrix (GLCM), grey-level run length matrix (GLRLM) and the grey-level size zone matrix (GLSZM), were computed from T2w images. Logistic regression models were trained using different feature subsets to classify each lesion as either HG or LG. To avoid overfitting, fivefold cross validation was applied on feature selection, model training and performance evaluation. Performance of all models generated was evaluated using the area under the curve (AUC) method. Results: Consistent with previous studies, ADC was found to discriminate between HG and LG with an AUC of 0.76. Of the three statistical TF families, GLCM (plus select mpMRI features including ADC) scored the highest AUC (0.84) with GLRLM plus mpMRI similarly performing well (AUC  =  0.82). When all TFs were considered in combination, an AUC of 0.91 (95% confidence interval 0.87-0.95) was achieved. Conclusions: Incorporating T2w TFs significantly improved model performance for classifying prostate tumour aggressiveness. This result, however, requires further validation in a larger patient cohort.

Revisiting quantitative multi-parametric MRI of benign prostatic hyperplasia and its differentiation from transition zone cancer

PURPOSE

This study investigates the multiparametric MRI (mpMRI) appearance of different types of benign prostatic hyperplasia (BPH) and whether quantitative mpMRI is effective in differentiating between prostate cancer (PCa) and BPH.

MATERIALS AND METHODS

Patients (n = 60) with confirmed PCa underwent preoperative 3T MRI. T2-weighted, multi-echo T2-weighted, diffusion weighted and dynamic contrast enhanced images (DCE) were obtained prior to undergoing prostatectomy. PCa and BPH (cystic, glandular or stromal) were identified in the transition zone and matched with MRI. Quantitative mpMRI metrics: T2, ADC and DCE-MRI parameters using an empirical mathematical model were measured.

RESULTS

ADC values were significantly lower (p < 0.001) in PCa compared to all BPH types and can differentiate between PCa and BPH with high accuracy (AUC = 0.87, p < 0.001). T2 values were significantly lower (p < 0.001) in PCa compared to cystic BPH only, while glandular (p = 0.27) and stromal BPH (p = 0.99) showed no significant difference from PCa. BPH mimics PCa in the transition zone on DCE-MRI evidenced by no significant difference between them. mpMRI values of glandular (ADC = 1.31 ± 0.22 µm²/ms, T2 = 115.7 ± 37.3 ms) and cystic BPH (ADC = 1.92 ± 0.43 µm²/ms, T2 = 242.8 ± 117.9 ms) are significantly different. There was no significant difference in ADC (p = 0.72) and T2 (p = 0.46) between glandular and stromal BPH.

CONCLUSIONS

Multiparametric MRI and specifically quantitative ADC values can be used for differentiating PCa and BPH, improving PCa diagnosis in the transition zone. However, DCE-MRI metrics are not effective in distinguishing PCa and BPH. Glandular BPH are not hyperintense on ADC and T2 as previously thought and have similar quantitative mpMRI measurements to stromal BPH. Glandular and cystic BPH appear differently on mpMRI and are histologically different.

Histogram analysis of prostate cancer on dynamic contrast-enhanced magnetic resonance imaging: A preliminary study emphasizing on zonal difference

Background

This study evaluated the performance of histogram analysis in the time course of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for differentiating cancerous tissues from benign tissues in the prostate.

Methods

We retrospectively analyzed the histograms of DCE-MRI of 30 patients. Histograms within regions of interest(ROI) in the peripheral zone (PZ) and transitional zone (TZ) were separately analyzed. The maximum difference wash-in slope (MWS) and delay phase slope (DPS) were defined for each voxel. Differences in histogram parameters, namely the mean, standard deviation (SD), the coefficient of variation (CV), kurtosis, skewness, interquartile range (IQR), percentile (P10, P25, P75, P90, and P90P10), Range, and modified full width at half-maximum (mFWHM) between cancerous and benign tissues were assessed.

Results

In the TZ, CV for ROIs of 7.5 and 10mm was the only significantly different parameter of the MWS (P = 0.034 and P = 0.004, respectively), whereas many parameters of the DPS (mean, skewness, P10, P25, P50, P75 and P90) differed significantly (P = <0.001–0.016 and area under the curve [AUC] = 0.73–0.822). In the PZ, all parameters of the MWS exhibited significant differences, except kurtosis and skewness in the ROI of 7.5mm(P = <0.001–0.017 and AUC = 0.865–0.898). SD, IQR, mFWHM, P90P10 and Range were also significant differences in the DPS (P = 0.001–0.035).

Conclusion

The histogram analysis of DCE-MRI is a potentially useful approach for differentiating prostate cancer from normal tissues. Different histogram parameters of the MWS and DPS should be applied in the TZ and PZ.

MpMRI of the prostate: is there a role for semi-quantitative analysis of DCE-MRI and late gadolinium enhancement in the characterisation of prostate cancer?

AIM

To assess whether there is a significant difference in perfusion parameters between benign and malignant prostatic lesions, focusing on semi-quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and presence of late gadolinium enhancement (LGE).

MATERIAL AND METHODS

Three hundred and thirteen patients who underwent multiparametric MRI (mpMRI) of the prostate and with available corresponding histology (prostatectomy or biopsy) were selected retrospectively for this study. The MRI protocol consisted of multiplanar T2-and diffusion-weighted imaging, DCE and delayed axial T1 images. Images were reviewed independently by two radiologists for LGE assessment and Prostate Imaging - Reporting and Data System (PI-RADS) scoring. For each lesion, semi-quantitative analysis of DCE-MRI was performed and the following data were evaluated: time to peak, wash-in rate, wash-out rate, brevity of enhancement, and area under the curve. The presence or absence of LGE in delayed axial T1 images was assessed qualitatively. MRI results were compared to histology. The presence of significant prostate cancer was based both on Epstein criteria (SPC) and Gleason score (GS ≥7).

RESULTS

SPC and Gleason score ≥7 tumours showed significant lower time to peak and brevity of enhancement (p<0.001) with higher wash-in rate (p=0.001). LGE was observed in 152/313 (49%) cases; among them 103/152 (68%) did not show SPC whereas 49/152 (32%) had SPC (p<0.001). The presence of LGE determined a risk reduction of SPC resulting as an independent predictor at multivariate analysis (logOR=-0.78, SE 0.33, p=0.02).

CONCLUSION

Semi-quantitative perfusion analysis and LGE may help to predict the presence/absence of a significant prostate tumour and represent a promising tool to improve mpMRI diagnostic performance.

Hypoenhancing prostate cancers on dynamic contrast-enhanced MRI are associated with poor outcomes in high-risk patients: results of a hypothesis generating study

PURPOSE

To investigate the association of hypoenhancement on dynamic Contrast enhanced (DCE) with prostate cancer patient outcomes.

MATERIAL AND METHODS

This was a single-institution retrospective Institutional Review Board (IRB)-approved cohort study of 54 men who had prostate Magnetic Resonance Imaging (MRI) within 6 months of cancer diagnosis between 01/2012 to 03/2014. Two readers independently identified the dominant MRI-lesions utilizing Prostate Imaging-Reporting and Data System-version2- guidelines. These lesions were classified as hypoenhancing or hyperenhancing, compared to normal peripheral zone using quantitative DCE analysis. The t test for unequal sample sizes and the two-sample Wilcoxon rank-sum tests were used to compare groups. Logistic regression determined if DCE characteristics predict the development of metastases or prostate cancer death.

RESULTS

Time-to-progression was significantly shorter for hypoenhancing tumors (6.2 vs. 24.8 months, p = 0.05). Men with these lesions had a higher odds of having poor outcome (univariate logistic regression, odds ratio (OR) 6.79, 95% confidence interval (CI) 1.45-31.72, p = 0.02; multivariate analysis, OR 2.05, 95% CI 0.30-13.72, p = 0.47). Hypoenhancing tumors were larger (33.1 vs. 19.1 mm, p < 0.001) and more likely to be intermediate (Gleason scores 3 + 4 and 4 + 3) and high-grade (Gleason scores ≥ 4 + 4) prostate cancers (p = 0.05). Men in the hypoenhancing group had a higher mean prostate-specific antigen (PSA) value (87.6 vs. 24.8 ng/dL, p = 0.01) and PSA density (1.54 vs. 0.72, p = 0.03). The mean K_trans and k_ep of hypoenhancing lesion were lower when compared to hyperenhancing lesions (p = 0.03 and p = 0.04). V_e values did not differ (p = 0.25).

CONCLUSION

Men with hypoenhancing prostate cancers may have a worse prognosis than men with hyperenhancing tumors.

Dynamic contrast-enhanced MRI perfusion of normal muscle in adult hips: Variation of permeability and semi-quantitative parameters

The purpose of this prospective study was to ascertain the degree of variation of semi-quantitative and permeability parameters on DCE-MRI of normally appearing striated muscles. Dynamic contrast-enhanced MRI of the right hip was performed in 20 women and 24 men. Mean age was 39.1 ± 12.4 years. Two regions of interest (ROI) were drawn in twelve muscles of anterior, medial and gluteal compartments: a free-form ROI covering the largest muscle section and a smaller elliptical ROI. Semi-quantitative and permeability parameters were calculated using the extended Tofts model. Statistical analysis was performed with a linear mixed model to assess perfusion parameters variation. Intra- and inter-observer agreements were assessed. The intra-observer agreement was considered to be good for free-form ROI (minimum Intra-Class Coefficient (ICC) = 0.72) and moderate for elliptical ROI (minimum ICC = 0.51), while the inter-observer agreement was considered to be bad in both cases (minimum ICC = 0.11). There was a high inter-individual variation in most of the perfusion parameters evaluated. The average coefficients of variation were: Time To Peak = 9%, Area Under the Curve = 44%, V_e = 61%, K_ep = 90%, Initial Slope = 99%, and K^trans = 128%. A considerable variation in resting muscle perfusion parameters was seen. This could lead to errors in the analysis of muscle DCE-MRI studies or oncologic/non oncologic studies using muscle as a referential. Further studies targeted on acquisition protocols and post-processing software are necessary to improve the performance of muscle MR perfusion.

Feasibility of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using Low-Dose Gadolinium: Comparative Performance With Standard Dose in Prostate Cancer Diagnosis

OBJECTIVES

This study investigates whether administration of low doses of gadolinium-based contrast agent (GBCA) for dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can be as effective as a standard dose in distinguishing prostate cancer (PCa) from benign tissue. In addition, we evaluated the combination of kinetic parameters from the low- and high-dose injection as a new diagnostic marker.

MATERIALS AND METHODS

Patients (n = 17) with histologically confirmed PCa underwent preoperative 3 T MRI. Dynamic contrast-enhanced MRI images were acquired at 8.3-second temporal resolution with a low dose (0.015 mmol/kg) and close to the standard dose (0.085 mmol/kg) of gadobentate dimeglumine bolus injections. Low-dose images were acquired for 3.5 minutes, followed by a 5-minute gap before acquiring standard dose images for 8.3 minutes. The data were analyzed qualitatively to investigate whether lesions could be detected based on early focal enhancement and quantitatively by fitting signal intensity as a function of time with an empirical mathematical model to obtain a maximum enhancement projection (MEP) and signal enhancement rate (α).

RESULTS

Both low- and standard-dose DCE-MRI showed similar sensitivity (13/26 = 50%) and lesion conspicuity score (4.0 ± 1.0 vs 4.2 ± 0.9; P = 0.317) for PCa diagnosis on qualitative analysis. Prostate cancer showed significantly increased α compared with benign tissue for low (9.98 ± 5.84 vs 5.12 ± 2.95 s) but not for standard (4.27 ± 2.20 vs 3.35 ± 1.48 s) dose. The ratio of low-dose α to standard-dose α was significantly greater (P = 0.02) for PCa (2.8 ± 2.3) than for normal prostate (1.6 ± 0.9), suggesting changes in water exchange and T2* effects associated with cancer. In addition, decreases in the percentage change in T1 relaxation rate as a function of increasing contrast media concentration (ie, the "saturation effect") can also contribute to the observed differences in high-dose and low-dose α. Area under the receiver operating characteristic curve for differentiating PCa from benign tissue using α was higher for low dose (0.769) compared with standard dose (0.625). There were no significant differences between MEP calculated for PCa and normal tissue at the low and standard doses. Moderate significant Pearson correlation for DCE parameters, MEP (r = 0.53) and α (r = 0.58), was found between low and standard doses of GBCA.

CONCLUSIONS

These preliminary results suggest that DCE-MRI with a low GBCA dose distinguishes PCa from benign prostate tissue more effectively than does the standard GBCA dose, based on signal enhancement rate. Diagnostic accuracy is similar on qualitative assessment. Prostate cancer diagnosis may be feasible with DCE-MRI with low-dose GBCA. In addition, comparison of enhancement kinetics after low and high doses of contrast media may provide diagnostically useful information.

Prostate DCE-MRI with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction using an approximated analytical approach

PURPOSE

To develop and evaluate a practical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method for prostate dynamic contrast-enhanced (DCE) MRI analysis.

THEORY

We proposed a simple analytical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method using a Taylor series approximation to the steady-state spoiled gradient echo signal equation. This approach only requires <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> maps and uncorrected pharmacokinetic (PK) parameters as input to estimate the corrected PK parameters.

METHODS

The proposed method was evaluated using a prostate digital reference object (DRO), and 82 in vivo prostate DCE-MRI cases. The approximated analytical correction was compared with the ground truth PK parameters in simulation, and compared with the reference numerical correction in in vivo experiments, using percentage error as the metric.

RESULTS

The prostate DRO results showed that our approximated analytical approach provided residual error less than 0.4% for both K^trans and v_e , compared to the ground truth. This noise-free residual error was smaller than the noise-induced error using the reference numerical correction, which had a minimum error of 2.1+4.3% with baseline signal-to-noise ratio of 234.5. For the 82 in vivo cases, K^trans and v_e percentage error compared to the reference numerical correction method had a mean of 0.1% (95% central range of [0.0%, 0.2%]) across the prostate volume.

CONCLUSION

The approximated analytical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction method provides comparable results with less than 0.2% error within 95% central range, compared to reference numerical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction. The proposed method is a practical solution for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>B</mml:mi> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo></mml:msubsup> </mml:mrow> </mml:math> correction in prostate DCE-MRI because of its simple implementation.

Quantitative parameters in dynamic contrast-enhanced magnetic resonance imaging for the detection and characterization of prostate cancer

Objectives

to assess the diagnostic accuracy of quantitative parameters of DCE-MRI in multi-parametric MRI (mpMRI) in comparison to the histopathology (including Gleason grade) of prostate cancer.

Patients and methods

150 men with suspected prostate cancer (abnormal digital rectum examination and or elevated prostate-specific antigen) received pre-biopsy 3T mpMRI and were recruited into peer-reviewed, protocol-based prospective study. The DCE-MRI quantitative parameters (K^trans (influx transfer constant) and k_ep (efflux rate constant)) of the cancerous and normal areas were recorded using four different kinetic models employing Olea Sphere (Olea Medical, La Ciotat, France). The correlation between these parameters and the histopathology of the lesions (biopsy and in a sub-cohort 41 radical prostatectomy specimen) was assessed.

Results

The quantitative parameters showed a significant difference between non-cancerous (benign) and cancerous lesions (Gleason score≥3+3) in the prostate gland. The cut-off values for prostate cancer differentiation were: K^trans (0.205 min⁻¹) and k_ep (0.665 min⁻¹) in the extended Tofts model (ET) and K^trans(0.205 min⁻¹ and k_ep (0.63 min⁻¹) in the Lawrence and Lee delay (LD) models respectively. The mean K^trans value also showed a difference between low-grade cancer (Gleason score=3+3) and high-grade cancer (Gleason score ≥ 3+4). With the addition of DCE-MRI quantitative parameters, the sensitivity of the PIRAD scoring system was increased from 56.6% to 92.1% (K^trans_ET), 93.1% (k_ep_ET), 91.0%, (K^trans_LD) and 89.4% (k_ep_LD).

Conclusion

Quantitative DCE-MRI parameters improved the diagnostic performance of conventional MRI in distinguishing normal and prostate cancers, including characterization of grade of cancers. The ET and LD models in post-image processing analysis provided better cut-off values for prostate cancer differentiation than the other quantitative DCE-MRI parameters.

Automatic Prostate Cancer Segmentation Using Kinetic Analysis in Dynamic Contrast-Enhanced MRI

BACKGROUND

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides functional information on the microcirculation in tissues by analyzing the enhancement kinetics which can be used as biomarkers for prostate lesions detection and characterization.

OBJECTIVE

The purpose of this study is to investigate spatiotemporal patterns of tumors by extracting semi-quantitative as well as wavelet-based features, both extracted from pixel-based time-signal intensity curves to segment prostate lesions on prostate DCE-MRI.

METHODS

Quantitative dynamic contrast-enhanced MRI data were acquired on 22 patients. Optimal features selected by forward selection are used for the segmentation of prostate lesions by applying fuzzy c-means (FCM) clustering. The images were reviewed by an expert radiologist and manual segmentation performed as the ground truth.

RESULTS

Empirical results indicate that fuzzy c-mean classifier can achieve better results in terms of sensitivity, specificity when semi-quantitative features were considered versus wavelet kinetic features for lesion segmentation (Sensitivity of 87.58% and 75.62%, respectively) and (Specificity of 89.85% and 68.89 %, respectively).

CONCLUSION

The proposed segmentation algorithm in this work can potentially be implemented for automatic prostate lesion detection in a computer aided diagnosis scheme and combined with morphologic features to increase diagnostic credibility.

Performance of Ultrafast DCE-MRI for Diagnosis of Prostate Cancer

RATIONALE AND OBJECTIVES

This study aimed to test high temporal resolution dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for different zones of the prostate and evaluate its performance in the diagnosis of prostate cancer (PCa). Determine whether the addition of ultrafast DCE-MRI improves the performance of multiparametric MRI.

MATERIALS AND METHODS

Patients (n = 20) with pathologically confirmed PCa underwent preoperative 3T MRI with T2-weighted, diffusion-weighted, and high temporal resolution (~2.2 seconds) DCE-MRI using gadoterate meglumine (Guerbet, Bloomington, IN) without an endorectal coil. DCE-MRI data were analyzed by fitting signal intensity with an empirical mathematical model to obtain parameters: percent signal enhancement, enhancement rate (α), washout rate (β), initial enhancement slope, and enhancement start time along with apparent diffusion coefficient (ADC) and T2 values. Regions of interests were placed on sites of prostatectomy verified malignancy (n = 46) and normal tissue (n = 71) from different zones.

RESULTS

Cancer (α = 6.45 ± 4.71 s^-1, β = 0.067 ± 0.042 s^-1, slope = 3.78 ± 1.90 s^-1) showed significantly (P <.05) faster signal enhancement and washout rates than normal tissue (α = 3.0 ± 2.1 s^-1, β = 0.034 ± 0.050 s^-1, slope = 1.9 ± 1.4 s^-1), but showed similar percentage signal enhancement and enhancement start time. Receiver operating characteristic analysis showed area under the curve for DCE parameters was comparable to ADC and T2 in the peripheral (DCE 0.67-0.82, ADC 0.80, T2 0.89) and transition zones (DCE 0.61-0.72, ADC 0.69, T2 0.75), but higher in the central zone (DCE 0.79-0.88, ADC 0.45, T2 0.45) and anterior fibromuscular stroma (DCE 0.86-0.89, ADC 0.35, T2 0.12). Importantly, combining DCE with ADC and T2 increased area under the curve by ~30%, further improving the diagnostic accuracy of PCa detection.

CONCLUSION

Quantitative parameters from empirical mathematical model fits to ultrafast DCE-MRI improve diagnosis of PCa. DCE-MRI with higher temporal resolution may capture clinically useful information for PCa diagnosis that would be missed by low temporal resolution DCE-MRI. This new information could improve the performance of multiparametric MRI in PCa detection.

A direct comparison of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging for prostate cancer detection and prediction of aggressiveness

INTRODUCTION

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) analyse tissue vascularization. We evaluated if CEUS can provide comparable information as DCE-MRI for the detection of prostate cancer (PCa) and prediction of its aggressiveness.

MATERIAL AND METHODS

A post-hoc evaluation of 92 patients was performed. In each patient CEUS and DCE-MRI parameters of the most suspicious lesion identified on MRI were analysed. The predictive values for discrimination between benign lesions, low-/intermediate- and high-grade PCa were evaluated. Results of targeted biopsy served as reference standard (benign lesions, n=51; low- and intermediate-grade PCa [Gleason grade group 1 and 2], n=22; high-grade PCa [≥ Gleason grade group 3], n=19).

RESULTS

In peripheral zone lesions of all tested CEUS parameters only time to peak (TTP_CEUS) showed significant differences between benign lesions and PCa (AUC 0.65). Of all tested DCE-MRI parameters, rate constant (K_ep) was the best discriminator of high-grade PCa in the whole prostate (AUC 0.83) and in peripheral zone lesions (AUC 0.89).

CONCLUSION

DCE-MRI showed a superior performance for detection of PCa and prediction of its aggressiveness. CEUS and DCE-MRI performed better in peripheral zone lesions than in transition zone lesions.

KEY POINTS

• DCE-MRI gathers information about vascularization and capillary permeability characteristics of tissues. • DCE-MRI can detect PCa and predict its aggressiveness. • CEUS also gathers information about vascularization of tissues. • For detection of PCa and prediction of aggressiveness DCE-MRI performed superiorly. • Both imaging techniques performed better in peripheral zone lesions.

Automatic Detection and Quantitative DCE-MRI Scoring of Prostate Cancer Aggressiveness

Purpose

To develop a robust and clinically applicable automated method for analyzing Dynamic Contrast Enhanced (DCE-) MRI of the prostate as a guide for targeted biopsies and treatments.

Materials and methods

An unsupervised pattern recognition (PR) method was used to analyze prostate DCE-MRI from 71 sequential radiotherapy patients. Identified regions of interest (ROIs) with increased perfusion were assigned either to the peripheral (PZ) or transition zone (TZ). Six quantitative features, associated with the washin and washout part of the weighted average DCE curve from the ROI, were calculated. The associations between the assigned DCE-scores and Gleason Score (GS) were investigated. A heatmap of tumor aggressiveness covering the entire prostate was generated and validated with histopathology from MRI-ultrasound fused (MRI-US) targeted biopsies.

Results

The volumes of the PR-identified ROI’s were significantly correlated with the highest GS from the biopsy session for each patient. Following normalization (and only after normalization) with gluteus maximus muscle’s DCE signal, the quantitative features in PZ were significantly correlated with GS. These correlations straightened in subset of patients with available MRI-US biopsies when GS from the individual biopsies were used. Area under the receiver operating characteristics curve for discrimination between indolent vs aggressive cancer for the significant quantitative features reached 0.88–0.95. When DCE-scores were calculated in normal appearing tissues, the features were highly discriminative for cancer vs no cancer both in PZ and TZ. The generated heatmap of tumor aggressiveness coincided with the location and GS of the MRI-US biopsies.

Conclusion

A quantitative approach for DCE-MRI analysis was developed. The resultant map of aggressiveness correlated well with tumor location and GS and is applicable for integration in radiotherapy/radiology imaging software for clinical translation.

DCE MRI of prostate cancer

DCE MRI is an established component of multi-parametric MRI of the prostate. The sequence highlights the vascularization of cancerous lesions, allowing readers to corroborate suspicious findings on T2W and DW MRI and to note subtle lesions not visible on the other sequences. In this article, we review the technical aspects, methods of evaluation, limitations, and future perspectives of DCE MRI.

Practical aspects of prostate MRI: hardware and software considerations, protocols, and patient preparation

The use of multiparametric MRI scans for the evaluation of men with prostate cancer has increased dramatically and is likely to continue expanding as new developments come to practice. However, it has not yet gained the same level of acceptance of other imaging tests. Partly, this is because of the use of suboptimal protocols, lack of standardization, and inadequate patient preparation. In this manuscript, we describe several practical aspects of prostate MRI that may facilitate the implementation of new prostate imaging programs or the expansion of existing ones.

Dynamic contrast-enhanced MRI of ocular melanoma

Dynamic contrast-enhanced MRI is used for the assessment of microvasculature in several tumours. We aimed to assess the contrast signal enhancement characteristics of ocular melanoma. Forty patients with ocular melanoma were prospectively investigated with ocular MRI including dynamic contrast-enhanced sequences over a 13-month period. A region-of-interest analysis of the images was carried out to calculate signal enhancement characteristics after a contrast injection. Clinical follow-up data such as extraocular spread and development of liver metastasis were compared with the signal enhancement characteristics of the ocular melanoma. In 39 patients (98%), the ocular melanomas showed an early strong signal enhancement after contrast injection, resulting in a mean time of maximum enhancement of 49 s. Clinical follow-up was available in 28 patients (70%) and indicated that the peak signal intensity was significantly increased (P=0.039) in patients who developed extraocular spread or liver metastasis at a later stage. Ocular melanoma shows signal enhancement characteristics of hypervascular neoplasms. This study provides baseline curve pattern data that may be useful for assessing changes in vascularity, for example during therapy response. Furthermore, the study showed that a strong signal enhancement of the ocular melanoma might be linked to a less favourable prognosis.

Can multiparametric MRI rule in or rule out significant prostate cancer?

PURPOSE OF REVIEW

To show how multiparametric MRI can rule in the presence of significant prostate cancer (PCa), allowing for magnetic resonance-targeted biopsies to detect aggressive tumors eligible for immediate treatment and to evaluate if mp-MRI can rule out significant tumor foci to avoid overdiagnosis and overtreatment of PCa.

RECENT FINDINGS

Diffusion-weighted MRI plays a major role to detect tumor foci and to rule in significant PCa. A low apparent diffusion coefficient (ADC) value indicates that high Gleason grade tumors are present. Conversely, the absence of any suspicious focus or foci with a high apparent diffusion coefficient value indicates either benign tissue or low-grade tumor

SUMMARY

mp-MRI Multiparametric MRI is a highly accurate filter to detect aggressive tumors and to avoid detection of insignificant cancer. There is growing evidence that it may be indicated in any man with an elevated Prostatic Specific Antigen level before considering whether an immediate biopsy should be performed or whether a simple follow-up should be the option.

False positive and false negative diagnoses of prostate cancer at multi-parametric prostate MRI in active surveillance

Abstract

MP-MRI is a critical component in active surveillance (AS) of prostate cancer (PCa) because of a high negative predictive value for clinically significant tumours. This review illustrates pitfalls of MP-MRI and how to recognise and avoid them. The anterior fibromuscular stroma and central zone are low signal on T2W-MRI/apparent diffusion coefficient (ADC), resembling PCa. Location, progressive enhancement and low signal on b ≥1000 mm²/s echo-planar images (EPI) are differentiating features. BPH can mimic PCa. Glandular BPH shows increased T2W/ADC signal, cystic change and progressive enhancement; however, stromal BPH resembles transition zone (TZ) PCa. A rounded morphology, low T2 signal capsule and posterior/superior location favour stromal BPH. Acute/chronic prostatitis mimics PCa at MP-MRI, with differentiation mainly on clinical grounds. Visual analysis of diffusion-weighted MRI must include EPI and appropriate windowing of ADC. Quantitative ADC analysis is limited by lack of standardization; the ADC ratio and ADC histogram analysis are alternatives to mean values. DCE lacks standardisation and has limited utility in the TZ, where T2W/DWI are favoured. Targeted TRUS-guided biopsies of MR-detected lesions are challenging. Lesions detected on MP-MRI may not be perfectly targeted with TRUS and this must be considered when faced with a suspicious lesion on MP-MRI and a negative targeted TRUS biopsy histopathological result.

Keypoints

• Multi-parametric MRI plays a critical role in prostate cancer active surveillance.

• Low T2W signal intensity structures appear dark on ADC, potentially simulating cancer.

• Stromal BPH mimics cancer at DWI and DCE.

• Long b value trace EPI should be reviewed

• Targeted biopsy of MR-detected lesions using TRUS guidance may be challenging.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

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.

Physiologic characterization of inflammatory arthritis in a rabbit model with BOLD and DCE MRI at 1.5 Tesla

OBJECTIVE

Our aim was to test the feasibility of blood oxygen level dependent magnetic resonance imaging (BOLD MRI) and dynamic contrast-enhanced (DCE) MRI to monitor periarticular hypoxic/inflammatory changes over time in a juvenile rabbit model of arthritis.

METHODS

We examined arthritic and contralateral nonarthritic knees of 21 juvenile rabbits at baseline and days 1,14, and 28 after induction of arthritis by unilateral intra-articular injection of carrageenin with BOLD and DCE MRI at 1.5 Tesla (T). Nine noninjected rabbits served as controls. Associations between BOLD and DCE-MRI and corresponding intra-articular oxygen pressure (PO2) and blood flow [blood perfusion units (BPU)] (polarographic probes, reference standards) or clinical-histological data were measured by correlation coefficients.

RESULTS

Percentage BOLD MRI change obtained in contralateral knees correlated moderately with BPU on day 0 (r = -0.51, p = 0.02) and excellently on day 28 (r = -0.84, p = 0.03). A moderate correlation was observed between peak enhancement DCE MRI (day 1) and BPU measurements in arthritic knees (r = 0.49, p = 0.04). In acute arthritis, BOLD and DCE MRI highly correlated (r = 0.89, p = 0.04; r = 1.0, p < 0.0001) with histological scores in arthritic knees.

CONCLUSION

The proposed techniques are feasible to perform at 1.5 T, and they hold potential as surrogate measures to monitor hypoxic and inflammatory changes over time in arthritis at higher-strength MRI fields.

KEY POINTS

• BOLD and DCE MRI detect interval perisynovial changes in a rabbit knee • BOLD and DCE MRI act as surrogate markers of physiologic changes in arthritis • BOLD MRI signal represents oxygen extraction compared with intra-articular PO 2 • DCE MRI measurements estimate physiologic periarticular vascular properties • In rabbit knees with acute arthritis, BOLD/DCE MRI highly correlated with histological scores.

Multi-parametric (mp) MRI of prostatic ductal adenocarcinoma

BACKGROUND

Prostatic ductal adenocarcinoma (DCa) is an aggressive variant of conventional adenocarcinoma (CCa) with mixed DCa and CCa tumors comprising up to 5% of all prostate cancers. DCa may be underestimated on T2-weighted (T2W) MRI. This study assessed the mp-MRI appearance of DCa as compared with CCa.

METHODS

With research ethics board approval, we identified 38 patients who underwent mp-MRI (T2W, DWI, and DCE) and radical prostatectomy (RP) between 2012 and 2014. Eight DCa in 8 patients and 39 CCa tumor foci in 30 consecutive patients were identified. Tumor volume, apparent diffusion coefficient (ADC;10(-3) mm(2) /s), and time-signal intensity (SI) curves were calculated. Parametric data were compared using the Kruskal-Wallis test and univariate regression. Time-SI curves were compared using the chi-square test.

RESULTS

Tumor volumes were: 1.62(±1.02) for DCa, 1.03(±0.54) for Gleason 9, 0.88(±0.93) for Gleason 7/8, and 0.26(±0.14) mL for Gleason 6. There was no difference in size between DCa and Gleason 9 (P = 0.22); however, DCa were larger than Gleason 7/8 (P = 0.03) and Gleason 6 (P = 0.003) tumors. ADC values were: 0.789(±0.22) for DCa, 1.01(±0.19) for Gleason 9, 0.992(±0.23) for Gleason 7/8 and 1.389(±0.41) 10(-3) mm(2) /s for Gleason 6 tumors. There was no difference in ADC between DCa and Gleason 9 (P = 0.14) or Gleason 7/8 (P = 0.055) tumors. There was a difference in ADC for DCa and Gleason ≥7 CCa compared to Gleason 6 tumors, (P < 0.001 and P = 0.012). All DCa demonstrated type III time-SI curves. Gleason ≥ 7 tumors demonstrated type II/III curves. Gleason 6 tumors demonstrated Type I/II time-SI curves. There was no difference in curve type between groups, (P = 0.18).

CONCLUSION

Although DCa mimics Gleason score 3 + 3 = 6 tumor at T2W MRI; DCa resembles Gleason ≥7 CCa on mp-MRI.

A comparison of arterial spin labeling perfusion MRI and DCE-MRI in human prostate cancer

Perfusion MRI has the potential to provide pathophysiological biomarkers for the evaluating, staging and therapy monitoring of prostate cancer. The objective of this study was to explore the feasibility of noninvasive arterial spin labeling (ASL) to detect prostate cancer in the peripheral zone and to investigate the correlation between the blood flow (BF) measured by ASL and the pharmacokinetic parameters K(trans) (forward volume transfer constant), kep (reverse reflux rate constant between extracellular space and plasma) and ve (the fractional volume of extracellular space per unit volume of tissue) measured by dynamic contrast-enhanced (DCE) MRI in patients with prostate cancer. Forty-three consecutive patients (ages ranging from 49 to 86 years, with a median age of 74 years) with pathologically confirmed prostate cancer were recruited. An ASL scan with four different inversion times (TI = 1000, 1200, 1400 and 1600 ms) and a DCE-MRI scan were performed on a clinical 3.0 T GE scanner. BF, K(trans), kep and ve maps were calculated. In order to determine whether the BF values in the cancerous area were statistically different from those in the noncancerous area, an independent t-test was performed. Spearman's bivariate correlation was used to assess the relationship between BF and the pharmacokinetic parameters K(trans), kep and ve. The mean BF values in the cancerous areas (97.1 ± 30.7, 114.7 ± 28.7, 102.3 ± 22.5, 91.2 ± 24.2 ml/100 g/min, respectively, for TI = 1000, 1200, 1400, 1600 ms) were significantly higher (p < 0.01 for all cases) than those in the noncancerous regions (35.8 ± 12.5, 42.2 ± 13.7, 53.5 ± 19.1, 48.5 ± 13.5 ml/100 g/min, respectively). Significant positive correlations (p < 0.01 for all cases) between BF and the pharmacokinetic parameters K(trans), kep and ve were also observed for all four TI values (r = 0.671, 0.407, 0.666 for TI = 1000 ms; 0.713, 0.424, 0.698 for TI = 1200 ms; 0.604, 0.402, 0.595 for TI = 1400 ms; 0.605, 0.422, 0.548 for TI = 1600 ms). It can be seen that the quantitative ASL measurements show significant differences between cancerous and benign tissues, and exhibit strong to moderate correlations with the parameters obtained using DCE-MRI. These results show the promise of ASL as a noninvasive alternative to DCE-MRI.

Dynamic contrast-enhanced MRI of the prostate with high spatiotemporal resolution using compressed sensing, parallel imaging, and continuous golden-angle radial sampling: preliminary experience

PURPOSE

To demonstrate dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate with both high spatial and temporal resolution via a combination of golden-angle radial k-space sampling, compressed sensing, and parallel-imaging reconstruction (GRASP), and to compare image quality and lesion depiction between GRASP and conventional DCE in prostate cancer patients.

MATERIALS AND METHODS

Twenty prostate cancer patients underwent two 3T prostate MRI examinations on separate dates, one using standard DCE (spatial resolution 3.0 × 1.9 × 1.9 mm, temporal resolution 5.5 sec) and the other using GRASP (spatial resolution 3.0 × 1.1 × 1.1 mm, temporal resolution 2.3 sec). Two radiologists assessed measures of image quality and dominant lesion size. The experienced reader recorded differences in contrast arrival times between the dominant lesion and benign prostate.

RESULTS

Compared with standard DCE, GRASP demonstrated significantly better clarity of the capsule, peripheral/transition zone boundary, urethra, and periprostatic vessels; image sharpness; and lesion conspicuity for both readers (P < 0.001-0.020). GRASP showed improved interreader correlation for lesion size (GRASP: r = 0.691-0.824, standard: r = 0.495-0.542). In 8/20 cases, only GRASP showed earlier contrast arrival in tumor than benign; in no case did only standard DCE show earlier contrast arrival in tumor.

CONCLUSION

High spatiotemporal resolution prostate DCE is possible with GRASP, which has the potential to improve image quality and lesion depiction as compared with standard DCE.

MRI in prostate cancer

Imaging studies play an important role in detection and management of prostate cancer and MRI especially with the use of endorectal coil because of high contrast resolution is recognized as the best imaging modality in evaluation of prostate cancer. Multiparametric MR study including T1 and T2 weighted images, diffusion weighted images, dynamic contrast study and MR spectroscopy is useful for detection and local staging of prostate cancer as well as posts treatment evaluation of patients either after surgery or radiation therapy for detection of local recurrence.

Prostate MRI: can we do without DCE sequences in 2013?

Multiparametric MRI (mp-MRI) of the prostate currently provides stable and reproducible performances. The usefulness of dynamic contrast-enhanced (DCE) sequences is currently challenged, as they sometimes only confirm what has already been observed on diffusion-weighted imaging (DWI) and require the additional purchase of a contrast agent. Eliminating these sequences may help accelerate the use of MRI in addition to, or in lieu of, prostate biopsies in selected patients. However, many studies show that these sequences can detect lesions invisible on T2-weighted and diffusion-weighted images, better assess cancer extension and aggressiveness, and finally help detecting recurrence after treatment. We present the various applications of dynamic MRI and discuss the possible consequences of its omission from the current protocol.

ACR Appropriateness Criteria prostate cancer--pretreatment detection, staging, and surveillance

Prostate cancer is the most common noncutaneous male malignancy in the United States. The use of serum prostate-specific antigen as a screening tool is complicated by a significant fraction of nonlethal cancers diagnosed by biopsy. Ultrasound is used predominately as a biopsy guidance tool. Combined rectal examination, prostate-specific antigen testing, and histology from ultrasound-guided biopsy provide risk stratification for locally advanced and metastatic disease. Imaging in low-risk patients is unlikely to guide management for patients electing up-front treatment. MRI, CT, and bone scans are appropriate in intermediate-risk to high-risk patients to better assess the extent of disease, guide therapy decisions, and predict outcomes. MRI (particularly with an endorectal coil and multiparametric functional imaging) provides the best imaging for cancer detection and staging. There may be a role for prostate MRI in the context of active surveillance for low-risk patients and in cancer detection for undiagnosed clinically suspected cancer after negative biopsy results. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T

BACKGROUND

A challenge in the diagnosis of prostate cancer (PCa) is the accurate assessment of aggressiveness.

OBJECTIVE

To validate the performance of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate at 3 tesla (T) for the assessment of PCa aggressiveness, with prostatectomy specimens as the reference standard.

DESIGN, SETTINGS, AND PARTICIPANTS

A total of 45 patients with PCa scheduled for prostatectomy were included. This study was approved by the institutional review board; the need for informed consent was waived.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Subjects underwent a clinical MRI protocol including DCE-MRI. Blinded to DCE-images, PCa was indicated on T2-weighted images based on histopathology results from prostatectomy specimens with the use of anatomical landmarks for the precise localization of the tumor. PCa was classified as low-, intermediate-, or high-grade, according to Gleason score. DCE-images were used as an overlay on T2-weighted images; mean and quartile values from semi-quantitative and pharmacokinetic model parameters were extracted per tumor region. Statistical analysis included Spearman's ρ, the Kruskal-Wallis test, and a receiver operating characteristics (ROC) analysis.

RESULTS AND LIMITATIONS

Significant differences were seen for the mean and 75th percentile (p75) values of wash-in (p = 0.024 and p = 0.017, respectively), mean wash-out (p = 0.044), and p75 of transfer constant (K(trans)) (p = 0.035), all between low-grade and high-grade PCa in the peripheral zone. ROC analysis revealed the best discriminating performance between low-grade versus intermediate-grade plus high-grade PCa in the peripheral zone for p75 of wash-in, K(trans), and rate constant (Kep) (area under the curve: 0.72). Due to a limited number of tumors in the transition zone, a definitive conclusion for this region of the prostate could not be drawn.

CONCLUSIONS

Quantitative parameters (K(trans) and Kep) and semi-quantitative parameters (wash-in and wash-out) derived from DCE-MRI at 3 T have the potential to assess the aggressiveness of PCa in the peripheral zone. P75 of wash-in, K(trans), and Kep offer the best possibility to discriminate low-grade from intermediate-grade plus high-grade PCa.

Comparative sensitivities of functional MRI sequences in detection of local recurrence of prostate carcinoma after radical prostatectomy or external-beam radiotherapy

OBJECTIVE

The aim of this retrospective study was to determine the respective accuracies of three types of functional MRI sequences-diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) MRI, and 3D (1)H-MR spectroscopy (MRS)-in the depiction of local prostate cancer recurrence after two different initial therapy options.

MATERIALS AND METHODS

From a cohort of 83 patients with suspicion of local recurrence based on prostate-specific antigen (PSA) kinetics who were imaged on a 3-T MRI unit using an identical protocol including the three functional sequences with an endorectal coil, we selected 60 patients (group A, 28 patients who underwent radical prostatectomy; group B, 32 patients who underwent external-beam radiation) who had local recurrence ascertained on the basis of a transrectal ultrasound-guided biopsy results and a reduction in PSA level after salvage therapy.

RESULTS

All patients presented with a local relapse. Sensitivity with T2-weighted MRI and 3D (1)H-MRS sequences was 57% and 53%, respectively, for group A and 71% and 78%, respectively, for group B. DCE-MRI alone showed a sensitivity of 100% and 96%, respectively, for groups A and B. DWI alone had a higher sensitivity for group B (96%) than for group A (71%). The combination of T2-weighted imaging plus DWI plus DCE-MRI provided a sensitivity as high as 100% in group B.

CONCLUSION

The performance of functional imaging sequences for detecting recurrence is different after radical prostatectomy and external-beam radiotherapy. DCE-MRI is a valid and efficient tool to detect prostate cancer recurrence in radical prostatectomy as well as in external-beam radiotherapy. The combination of DCE-MRI and DWI is highly efficient after radiation therapy. Three-dimensional (1)H-MRS needs to be improved. Even though it is not accurate enough, T2-weighted imaging remains essential for the morphologic analysis of the area.

Overview of dynamic contrast-enhanced MRI in prostate cancer diagnosis and management

OBJECTIVE

This article is a primer on the technical aspects of performing a high-quality dynamic contrast-enhanced MRI (DCE-MRI) examination of the prostate gland.

CONCLUSION

DCE-MRI is emerging as a useful clinical technique as part of a multi-parametric approach for evaluating the extent of primary and recurrent prostate cancer. Performing a high-quality DCE-MRI examination requires a good understanding of the technical aspects and limitations of image acquisition and postprocessing techniques.

Magnetic resonance tumor targeting imaging using gadolinium labeled human telomerase reverse transcriptase antisense probes

To develop a molecular probe for MRI detection of human tumor telomerase reverse transcriptase (hTERT) mRNA expression. Uniformly phosphorothioate-modified hTERT antisense oligonucleotide (ASON) homing hTERT mRNA was labeled with gadolinium (Gd) through the bifunctional chelator 1,4,7, 10-tetraazacyclododecane-N, N', N'', N'''-tetraacetic acid (DOTA) stirred within 45 minutes at 60 °C. The Gd labeled probes were characterized in vitro. The cellular uptake rate and biodistribution of (99m) Tc-DOTA-ASON was measured instead of that of Gd-DOTA-ASON. A549 lung adenocarcinoma model was established in BALB/c nude mice and Gd-DOTA-ASON was injected intraperitoneally and MR images were acquired using 7.0T Micro-MRI (Bruker Biospec, Ettlingen, Germany) at different time points. Immunohistochemical analysis of telomerase activity of each xenograft was operated two days after in vivo imaging. The binding efficiency of Gd-DOTA-ASON reached as high as 71.7 ± 4.5% (n = 6). Gd-DOTA-ASON displayed perfect stability in fresh human serum at 37 °C for 24 h. Compared with normal lung cells, A549 cells showed an obviously higher uptake of (99m) Tc-DOTA-ASON than that of lung cells (10.5 ± 2.7% vs. 4.8 ± 2.6%, P < 0.05). The signal intensity of A549 xenografts can be enhanced by Gd-DOTA-ASON and the signal to noise ratio (SNR) of tumor to muscle reached 2.37 and maintained a relatively high level within 6 h after injection. The activity of hTERT in A549 tumors can be suppressed by Gd-DOTA-ASON in pathological slices. The results of this study show that Gd-DOTA-ASON can be a promising intracellular MR contrast probe for targeting telomerase-positive carcinomas.