DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness

Can dynamic contrast enhanced MRI predict gleason score in prostate cancer? a systematic review and meta analysis

BACKGROUND AND OBJECTIVES

Multiparametric MRI has become a corner stone in diagnosis of prostate cancer (PC). DCE-MRI is used to quantify the influx of contrast media into tissues, which was shown to correlate with histopathology features. The present analysis sought to correlate DCE-MRI parameters with Gleason score (GS) based upon a large patient sample.

MATERIAL AND METHODS

MEDLINE library, Cochrane and SCOPUS databases were screened for the associations between DCE-MRI and GS in PC up to April 2020. The primary endpoint of the systematic review was the correlation between DCE-MRI parameters and GS and mean K^trans and K_ep and V_e values with standard deviation. In total, 13 studies with overall 894 patients were suitable for the analysis and included into the present study.

RESULTS

The highest correlation was identified for K^trans with a pooled correlation coefficient of r = 0.36 (95% CI 0.14-0.59). A large overlap was identified between clinical significant and non-significant PC for all DCE-parameters, for K^trans the pooled mean value of clinically non-significant PC was 0.32 min^-1 [95% CI 0.13-0.51] and for clinically significant PC it was 0.45 min^-1 (95% CI 0.25-0.64).

CONCLUSION

DCE-MRI cannot be used to predict GS in PC, and consequently cannot discriminate clinically significant from non-significant cancers.

Signal intensity form of the Tofts model for quantitative analysis of prostate dynamic contrast enhanced MRI data

The aim of this study is to develop a signal intensity (S(t)) form of the standard Tofts pharmacokinetic model that avoids the need to calculate tissue contrast agent concentration (C(t)) as function of time (t). We refer to this as 'SI-Tofts' model. Physiological parameters (K ^trans and v _e) calculated using the SI-Tofts and standard Tofts models were compared by using simulations and human prostate dynamic contrast enhanced (DCE) MRI data. This approach was also applied to the Patlak model to compare K ^trans values calculated from C(t) and S(t). Simulations were performed on DCE-MRI data from the quantitative imaging biomarkers alliance to validate SI-Tofts model. In addition, ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The C(t) was calculated for each ROI using the standard model with measured pre-contrast tissue T ₁ values. Both the simulation and clinical results showed strong correlation (r = 0.87-0.99, p < 0.001) for K ^trans and v _e calculated from the SI-Tofts and standard Tofts models. The SI-Tofts model with a correction factor using the T ₁ ratio of blood to tissue significantly improved the K ^trans estimates. The correlation of K ^trans obtained from the Patlak model with C(t) vs S(t) was also strong (r = 0.95-0.99, p < 0.001). These preliminary results suggest that physiological parameters from DCE-MRI can be reliably estimated from the SI-Tofts model without contrast agent concentration calculation.

WITHDRAWN: The Changes of ADC Value, DCE-MRI Parameters and Their Influence on Neuropsychology in Prostate Cancer Patients after Endocrine Therapy Based on Magnetic Resonance Imaging

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Luminal Water Imaging: Comparison With Diffusion-Weighted Imaging (DWI) and PI-RADS for Characterization of Prostate Cancer Aggressiveness

BACKGROUND

Luminal water imaging (LWI), a multicomponent T₂ mapping technique, has shown promise for prostate cancer (PCa) detection and characterization.

PURPOSE

To 1) quantify LWI parameters and apparent diffusion coefficient (ADC) in PCa and benign peripheral zone (PZ) tissues; and 2) evaluate the diagnostic performance of LWI, ADC, and PI-RADS parameters for differentiation between low- and high-grade PCa lesions.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-six PCa patients undergoing prostatectomy (mean age 59 years, range 46-72 years).

FIELD STRENGTH/SEQUENCE

Multiparametric MRI at 3.0T, including diffusion-weighted imaging (DWI) and LWI T₂ mapping.

ASSESSMENT

LWI parameters and ADC were quantified in index PCa lesions and benign PZ.

STATISTICAL TESTS

Differences in MRI parameters between PCa and benign PZ were assessed using Wilcoxon signed tests. Spearman correlation of pathological grade group (GG) with LWI parameters, ADC, and PI-RADS was evaluated. The utility of each of the parameters for differentiation between low-grade (GG ≤2) and high-grade (GG ≥3) PCa was determined by Mann-Whitney U tests and ROC analyses.

RESULTS

Twenty-six index lesions were analyzed (mean size 1.7 ± 0.8 cm, GG: 1 [n = 1; 4%], 2 [n = 14, 54%], 3 [n = 8, 31%], 5 [n = 3, 12%]). LWI parameters and ADC both showed high diagnostic performance for differentiation between benign PZ and PCa (highest area under the curve [AUC] for LWI parameter T_2,short [AUC = 0.98, P < 0.001]). The LWI parameters luminal water fraction (LWF) and amplitude of long T₂ component A_long significantly correlated with GG (r = -0.441, P = 0.024 and r = -0.414, P = 0.036, respectively), while PI-RADS, ADC, and the other LWI parameters did not (P = 0.132-0.869). LWF and A_long also showed significant differences between low-grade and high-grade PCa (AUC = 0.776, P = 0.008 and AUC = 0.758, P = 0.027, respectively). Maximum diagnostic performance for discrimination of high-grade PCa was found with combined LWI parameters (AUC 0.891, P = 0.001).

DATA CONCLUSION

LWI parameters, in particular in combination, showed superior diagnostic performance for differentiation between low-grade and high-grade PCa compared to ADC and PI-RADS assessment. J. Magn. Reson. Imaging 2020;52:271-279.

The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study

Objective

Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE).

Materials and methods

The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately.

Results

Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively.

Conclusion

DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.

Dynamic contrast-enhanced magnetic resonance imaging for differentiating osteomyelitis from acute neuropathic arthropathy in the complicated diabetic foot

OBJECTIVE

The main purpose of this study was to investigate the diagnostic value of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating osteomyelitis from acute neuropathic arthropathy in the diabetic foot.

MATERIALS AND METHODS

This prospective study was carried out on 30 diabetic foot patients, with a mean age of 51 years. The patients all underwent clinical examinations, laboratory examinations and DCE-MRI. The DCE-MRI parameters (K^trans, K_ep and V_e) of the regions of acute neuropathic arthropathy and osteomyelitis were calculated. Receiver operating characteristic curves (ROCs) were used to identify the DCE-MRI parameters that showed the highest accuracy in differentiating the acute neuropathic arthropathy from the osteomyelitic regions. Pearson correlation coefficients were used to assess the correlations among the DCE-MRI parameters, the level of C-reactive protein (CRP) and the erythrocyte sedimentation rate (ESR).

RESULTS

The K^trans, K_ep and V_e values of the osteomyelitic regions were higher than those of the acute neuropathic arthropathy regions, and significant differences were found between the two groups (P = 0.000, P = 0.000, P = 0.000). The ROC analysis showed that K^trans and V_e performed best in differentiating osteomyelitis from acute neuropathic arthropathy, both with an area under the curve of 0.938. The Pearson correlation coefficients showed that the DCE-MRI parameters correlated significantly with the level of CRP and ESR (P = 0.000, P = 0.014, P = 0.000; P = 0.000, P = 0.000, P = 0.013).

CONCLUSIONS

Our results showed that DCE-MRI may provide reproducible parameters that can reliably differentiate osteomyelitis from acute neuropathic arthropathy.

Diffusion and perfusion MRI quantification in ileal Crohn's disease

OBJECTIVES

To quantify intravoxel incoherent motion (IVIM)-DWI and dynamic contrast-enhanced (DCE)-MRI parameters in normal and abnormal ileal segments in Crohn's disease (CD) patients and to assess the association of these parameters with clinical and MRI-based measurements of CD activity.

METHODS

In this prospective study, 27 CD patients (M/F 18/9, mean age 42 years) underwent MR enterography, including IVIM-DWI and DCE-MRI. IVIM-DWI and DCE-MRI parameters were quantified in normal and abnormal small bowel segments, the latter identified by the presence of inflammatory changes. MRI parameter differences between normal and abnormal bowel were tested using Wilcoxon signed-rank tests. IVIM-DWI and DCE-MRI parameters were correlated with clinical data (C-reactive protein, Harvey-Bradshaw Index), conventional MRI parameters (wall thickness, length of involvement) and MRI activity scores (MaRIA, Clermont). Diagnostic performance of (combined) parameters for differentiation between normal and abnormal bowel was determined using ROC analysis.

RESULTS

The DCE-MRI parameters peak concentration C_peak, upslope, area-under-the-curve at 60s (AUC60), K^trans and v_e were significantly increased (p<0.023), while IVIM-DWI parameters perfusion fraction (PF) and ADC were significantly decreased (p<0.001) in abnormal bowel segments. None of the DCE-MRI and IVIM-DWI parameters correlated with clinical parameters (p>0.105). DCE-MRI parameters exhibited multiple significant correlations with wall thickness (C_peak, upslope, AUC60, K^trans; r range 0.431-0.664, p<0.025) and MaRIA/Clermont scores (C_peak, AUC60, K^trans; r range 0.441-0.617, p<0.021). Combined K^trans+v_e+PF+ADC showed highest AUC (0.963) for differentiation between normal and abnormal bowel, while ADC performed best for individual parameters (AUC=0.800).

CONCLUSIONS

DCE-MRI and IVIM-DWI, particularly when used in combination, are promising for non-invasive evaluation of small bowel CD.

KEY POINTS

• IVIM-DWI and DCE-MRI parameters were significantly different between normal and abnormal bowel segments in CD patients. • DCE-MRI parameters showed a significant association with wall thickness and MRI activity scores. • Combination of IVIM-DWI and DCE-MRI parameters led to the highest diagnostic performance for differentiation between normal and abnormal bowel segments, while ADC showed the highest diagnostic performance of individual parameters.

Comparison of region-of-interest-averaged and pixel-averaged analysis of DCE-MRI data based on simulations and pre-clinical experiments

Differences between region-of-interest (ROI) and pixel-by-pixel analysis of dynamic contrast enhanced (DCE) MRI data were investigated in this study with computer simulations and pre-clinical experiments. ROIs were simulated with 10, 50, 100, 200, 400, and 800 different pixels. For each pixel, a contrast agent concentration as a function of time, C(t), was calculated using the Tofts DCE-MRI model with randomly generated physiological parameters (K ^trans and v _e) and the Parker population arterial input function. The average C(t) for each ROI was calculated and then K ^trans and v _e for the ROI was extracted. The simulations were run 100 times for each ROI with new K ^trans and v _e generated. In addition, white Gaussian noise was added to C(t) with 3, 6, and 12 dB signal-to-noise ratios to each C(t). For pre-clinical experiments, Copenhagen rats (n  =  6) with implanted prostate tumors in the hind limb were used in this study. The DCE-MRI data were acquired with a temporal resolution of ~5 s in a 4.7 T animal scanner, before, during, and after a bolus injection (<5 s) of Gd-DTPA for a total imaging duration of ~10 min. K ^trans and v _e were calculated in two ways: (i) by fitting C(t) for each pixel, and then averaging the pixel values over the entire ROI, and (ii) by averaging C(t) over the entire ROI, and then fitting averaged C(t) to extract K ^trans and v _e. The simulation results showed that in heterogeneous ROIs, the pixel-by-pixel averaged K ^trans was ~25% to ~50% larger (p  <  0.01) than the ROI-averaged K ^trans. At higher noise levels, the pixel-averaged K ^trans was greater than the 'true' K ^trans, but the ROI-averaged K ^trans was lower than the 'true' K ^trans. The ROI-averaged K ^trans was closer to the true K ^trans than pixel-averaged K ^trans for high noise levels. In pre-clinical experiments, the pixel-by-pixel averaged K ^trans was ~15% larger than the ROI-averaged K ^trans. Overall, with the Tofts model, the extracted physiological parameters from the pixel-by-pixel averages were larger than the ROI averages. These differences were dependent on the heterogeneity of the ROI.