Multiparametric magnetic resonance imaging for transition zone prostate cancer: essential findings, limitations, and future directions

Comparison of Ga-68 PSMA PET/CT and Multiparametric MRI for Initial Detection and Staging of Prostate Cancer

Background  Multiparametric magnetic resonance imaging (mpMRI) is widely used for the evaluation of prostate cancer and is known to have better accuracy. Gallium-68 prostate-specific membrane antigen (Ga-68 PSMA) is a radiotracer that shows high localization in prostate cancer cells. Purpose  The purpose of this study was to assess the sensitivity and utility of Ga-68 PSMA positron emission tomography/computed tomography (PET/CT) in comparison with mpMRI as a noninvasive imaging technique for the initial diagnosis and locoregional staging of prostate cancer using transrectal ultrasound (TRUS)-guided biopsy as gold standard. Materials and Methods  This prospective observational study conducted from August 2017 to April 2020 evaluated 60 men ( n  = 60) with biopsy-proven prostate carcinoma. They underwent mpMRI and Ga-68 PSMA PET/CT scans within 14 days with TRUS biopsy being gold standard. T staging of disease, N staging of lymph nodes within the pelvis, and M staging of lesions in pelvic bones (within the imaging field of mpMRI) were compared using PSPP version 1.0.1 statistical software. Results  All 60 men with a mean age of 69.9 ± 9.35 years showed Ga-68 PSMA avid disease, whereas 55 were detected by mpMRI. The sensitivity in detection of prostate lesions (with 95% confidence interval) was 99.08% for Ga-68 PSMA PET/CT and 84.40% for mpMRI. Ga-68 PSMA PET/CT detected greater number of patients with regional lymph nodal involvement (19/60) as compared with mpMRI (12/60). Ga-68 PSMA PET/CT showed PSMA avid pelvic skeletal lesions in nine patients, whereas mpMRI detected pelvic lesions in six patients. In addition, four other patients showed extrapelvic skeletal lesions on Ga-68 PSMA PET/CT. Conclusion  Ga-68 PSMA PET/CT has superior sensitivity in detection of primary prostate tumor, as compared with mpMRI. Both modalities correlate well in detection of seminal vesicle involvement. Ga-68 PSMA PET/CT outperformed mpMRI in detection of lymph nodal and skeletal metastases. Hence, Ga-68 PSMA PET/CT should be considered as first-line diagnostic modality for carcinoma prostate. Summary Statement : Ga-68 PSMA PET/CT shows superior diagnostic performance than mpMRI in the evaluation of prostate cancer.

Artificial Intelligence Algorithm-Based MRI for Differentiation Diagnosis of Prostate Cancer

The rapid increase in prostate cancer (PCa) patients is similar to that of benign prostatic hyperplasia (BPH) patients, but the treatments are quite different. In this research, magnetic resonance imaging (MRI) images under the weighted low-rank matrix restoration algorithm (RLRE) were utilized to differentiate PCa from BPH. The diagnostic effects of different sequences of MRI images were evaluated to provide a more effective examination method for the clinical differential diagnosis of PCa and BPH. 150 patients with suspected PCa were taken as the research objects. Pathological examination revealed that 137 patients had PCa and 13 patients had BPH. The pathological results were the gold standard and were compared with the MRI results of different sequences. Therefore, the accuracy of the MRI results was evaluated. The results showed that with the rise of Gaussian noise, the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) of all three algorithms gradually decreased, but the PSNR and SSIM of the RLRE algorithm were always higher than those of the RL and BM3D algorithms (P < 0.05). The sensitivity (97.08%), specificity (92.31%), accuracy (96.67%), and consistency (0.678) of the dynamic contrast enhancement (DCE) sequence were higher than those of the plain scan (86.13%, 69.23%, 84.67%, and 0.469, respectively). In conclusion, the RLRE algorithm could promote the resolution of MRI images and improve the display effect. DCE could better differentiate PCa from BPH, had great clinical application value, and was worthy of clinical promotion.

Differentiation of Prostate Cancer and Stromal Hyperplasia in the Transition Zone With Monoexponential, Stretched-Exponential Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging in a Reduced Number of b Values: Correlation With Whole-Mount Pathology

OBJECTIVES

The aims of the study were to explore the feasibility of generating a monoexponential model (MEM), stretched-exponential model (SEM) based diffusion-weighted imaging (DWI), and diffusion kurtosis imaging (DKI) by applying the same set of reduced b values and to compare their effectiveness in distinguishing prostate cancer from stromal hyperplasia (SH) in the transition zone (TZ) area.

METHODS

An analysis of 75 patients who underwent preoperative DWI (b values of 0, 700, 1400, 2000 s/mm2) was performed. All lesions were localized on magnetic resonance images according to whole-mount histopathological correlations. The apparent diffusion coefficient (ADC), water molecular diffusion heterogeneity index (α), distributed diffusion coefficient (DDC), mean diffusivity (MD), and mean kurtosis (MK) values were calculated and compared between the TZ cancer and SH groups. Receiver operating characteristic analysis and areas under the receiver operating characteristic curve (AUCs) were carried out for all parameters.

RESULTS

Compared with the SH group, the ADC, DDC, α, and MD values of the TZ cancer group were significantly reduced, while the MK value was significantly increased (all P < 0.05). The AUCs of the ADC, DDC, α, MD, and MK were 0.828, 0.801, 0.813, 0.822, and 0.882, respectively. The AUC of MK was significantly higher than that of the other parameters (all P < 0.05).

CONCLUSIONS

When using the reduced b-value set, all parameters from MEM, SEM, based DWI, and DKI can effectively distinguish TZ cancer from SH. Among them, DKI demonstrated potential clinical superiority over the others in TZ cancer diagnosis.

Noninferiority of Monoparametric MRI Versus Multiparametric MRI for the Detection of Prostate Cancer: Diagnostic Accuracy of ADC Ratios Based on Advanced "Zoomed" Diffusion-Weighted Imaging

OBJECTIVES

The aim of this study was to compare the diagnostic accuracy of apparent diffusion coefficient (ADC) ratios as a monoparametric magnetic resonance imaging (MRI) protocol for the detection of prostate cancer (PCa) with the established multiparametric (mp) MRI at 3.0 T.

MATERIALS AND METHODS

According to power analysis, 52 male patients were included in this monocenter study with prospective data collection and retrospective, blinded multireader image analysis. The study was approved by the local ethics committee. Patients were recruited from January to December 2020. Based on mpMRI findings, patients underwent in-bore MR biopsy or prostatectomy for histopathologic correlation of suspicious lesions. Three readers, blinded to the histopathologic results and images of mpMRI, independently evaluated ADC maps for the detection of PCa. The ADC ratio was defined as the lowest signal intensity (SI) of lesions divided by the SI of normal tissue in the zone of origin. Predictive accuracy of multiparametric and monoparametric MRI were compared using logistic regression analysis. Moreover, both protocols were compared applying goodness-of-fit analysis with the Hosmer-Lemeshow test for continuous ADC ratios and Pearson χ2 test for binary decision calls, correlation analysis with Spearman ρ and intraclass correlation coefficients, as well as noninferiority assessment with a TOST ("two one-sided test").

RESULTS

Eighty-one histopathologically proven, unique PCa lesions (Gleason score [GS] ≥ 3 + 3) in 52 patients could be unequivocally correlated, with 57 clinically significant (cs) PCa lesions (GS ≥ 3 + 4). Multiparametric MRI detected 95%, and monoparametric ADC detected ratios 91% to 93% of csPCa. Noninferiority of monoparametric MRI was confirmed by TOST (P < 0.05 for all comparisons). Logistic regression analysis revealed comparable predictive diagnostic accuracy of ADC ratios (73.7%-87.8%) versus mpMRI (72.2%-84.7%). Spearman rank correlation coefficient for PCa aggressiveness revealed satisfactory correlation of ADC ratios (P < 0.013 for all correlations). The Hosmer-Lemeshow test for the logistic regression analysis for continuous ADC ratios indicated adequate predictive accuracy (P = 0.55-0.87), and the Pearson χ2 test showed satisfactory goodness of fit (P = 0.35-0.69, χ2 = 0.16-0.87).

CONCLUSIONS

Normalized ADC ratios based on advanced DWI are noninferior to mpMRI at 3.0 T for the detection of csPCa in a preselected patient cohort and proved a fast and accurate assessment tool, thus showing a potential prospect of easing the development of future screening methods for PCa.

Comparison between 18 F-DCFPyL PET and MRI for the detection of transition zone prostate cancer

BACKGROUND

We aimed to compare the diagnostic performance of ¹⁸ F-DCFPyL positron emission tomography (PET) and multiparameter magnetic resonance imaging (mp-MRI) in detecting transition zone (TZ) prostate cancer (PCa).

METHODS

This retrospective study included 20 patients who underwent ¹⁸ F-DCFPyL PET/MRI and 32 patients who underwent ¹⁸ F-DCFPyL PET/CT and MRI from January 2019 to June 2020. All patients had TZ lesions and underwent prostate biopsies. One senior (reader 1) and one junior (reader 2) nuclear medicine physician evaluated each TZ lesion independently, according to the molecular imaging prostate-specific membrane antigen scoring system and the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). The histologic diagnosis of prostate biopsy was used as the reference standard. The diagnostic performance of the two methods was compared in terms of inter-reader agreement and area under the receiver operating characteristic (AUC-ROC) curve.

RESULTS

Of the 52 patients, 43 had TZ PCa. For inter-reader agreement, the kappa value was 0.883 for ¹⁸ F-DCFPyL PET and 0.393 for mp-MRI. For PET, both readers had the same diagnostic sensitivity, specificity, and accuracy of 93.0%, 77.8%, and 90.4%, respectively. For mp-MRI, the diagnostic sensitivity, specificity, and accuracy was 67.4%, 33.3%, and 61.5% for reader 1, and 51.2%, 44.4%, and 51.9% for reader 2, respectively. PET outperformed mp-MRI for both readers with an AUC of 0.872 for PET versus 0.584 for mp-MRI, p = .0209 for reader 1, and an AUC of 0.860 for PET versus 0.505 for mp-MRI, p = .0213 for reader 2. Among the 43 patients with TZ PCa, ¹⁸ F-DCFPyL PET detected a distant bone metastasis missed by the CT in one case and two small lymph node metastases missed by the CT and MRI in another case.

CONCLUSIONS

These results suggest that ¹⁸ F-DCFPyL PET, which was almost independent of the experience of the readers, was more objective in the evaluation of TZ lesions, and had higher diagnostic value than mp-MRI.

Application of hierarchical clustering to multi-parametric MR in prostate: Differentiation of tumor and normal tissue with high accuracy

PURPOSE

Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretable way, in contrast to deep learning (DL) techniques.

METHODS

HC was constructed using mp-MR including intravoxel incoherent motion, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI from 40 tumor and normal tissues in peripheral zone (PZ) and 23 tumor and normal tissues in transition zone (TZ). HC model was optimized by assessing the combinations of several dissimilarity and linkage methods. Goodness of HC model was validated by internal methods.

RESULTS

Accuracy for differentiating tumor and normal tissue by optimal HC model was 96.3% in PZ and 97.8% in TZ, comparable to current clinical standards. Relationship between input (DWI and permeability parameters) and output (tumor and normal tissue cluster) was shown by heat maps, consistent with literature.

CONCLUSION

HC can accurately differentiate PCa and normal tissue, comparable to state-of-the-art diffusion based parameters. Contrary to DL techniques, HC is an operator-independent ML technique producing results that can be interpreted such that the results can be knowledgeably judged.

Detectability of prostate cancer in different parts of the gland with 3-Tesla multiparametric magnetic resonance imaging: correlation with whole-mount histopathology

BACKGROUND

We investigated whether the detectability of prostate cancer with 3-Tesla (3T) multiparametric magnetic resonance imaging (mpMRI) differs by tumor location.

METHODS

We identified 136 patients with prostate cancer who underwent 3-T mpMRI before prostatectomy at a single academic center. Two uroradiologists scored all MRIs with Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2). A genitourinary pathologist mapped tumor foci from serial whole-mount radical prostatectomy sections. We assessed concordance of images with cancer sites. Tumor foci with Gleason score ≥  3 + 4 or volume ≥ 0.5 mL were considered significant.

RESULTS

A total of 122 foci in 106 cases were identified with mpMRI. Twenty-four were PI-RADS 3, 52 were 4, and 46 were 5. A total of 274 tumor foci were identified with whole-mount pathology. The sensitivity stratified by location to detect significant cancer with a PI-RADS cutoff value of 3 was 56.0% overall, 50.0% in the peripheral zone (PZ), 71.2% in the transitional zone (TZ), 62.4% anterior, 49.5% posterior, 42.0% apical, 63.6% in the midgland, and 43.8% in the gland base. In multivariate analysis, tumor location was not a significant predictor of identification by mpMRI. Tumor volume, Gleason score, and index tumor status were significantly associated with identification by mpMRI.

CONCLUSIONS

mpMRI detected the majority of high-grade and large cancers, but had low sensitivity in the PZ, posterior, and apex and base of the gland. The high prevalence of low-volume, low-Gleason score index tumors, as well as satellite tumors in those areas, accounted for the difference.

An inter-centre statistical scale standardisation for quantitatively evaluating prostate tissue on T2-weighted MRI

Magnetic resonance images (MRI) require intensity standardisation if they are used for the purpose of quantitative analysis as inherent variations in image intensity levels between different image sets are manifest due to technical factors. One approach is to standardise the image intensity values using a statistically applied biological reference tissue. The aim of this study is to compare the performance of differing candidate biological reference tissues for standardising T2WI intensity distributions. Fifty-one prostate cancer patients across two centres with different scanners were evaluated using the percentage interpatient coefficient of variation (%interCV) for four different biological references; femoral bone marrow, ischioanal fossa, obturator-internus muscle and bladder urine. The tissue with the highest reproducibility (lowest %interCV) in both centres was used for intensity standardisation of prostate T2WI using three different statistical measures (mean, Z-score, median + Interquartile Range). The performance of different standardisation methods was evaluated from the assessment of image intensity histograms and the percentage normalised root mean square error (%NRSME) of the healthy peripheral zone tissue. Ischioanal fossa as a reference tissue demonstrated the highest reproducibility with %interCV of 18.9 for centre1 and 11.2 for centre2. Using ischioanal fossa for statistical intensity standardisation and the median + Interquartile Range method demonstrated the lowest %NRMSE across centres for healthy peripheral zone tissues. This study demonstrates ischioanal fossa as a preferred reference tissue for standardising intensity values from T2WI of the prostate. Subsequent image standardisation using the median + Interquartile Range intensity of the reference tissue demonstrated a robust and reliable standardisation method for quantitative image assessment.