Monitoring radiotherapy induced tissue changes in localized prostate cancer by multi-parametric magnetic resonance imaging (MP-MRI)

MRI and PSMA PET/CT of Biochemical Recurrence of Prostate Cancer

Prostate cancer may recur several years after definitive treatment, such as prostatectomy or radiation therapy. A rise in serum prostate-specific antigen (PSA) level is the first sign of disease recurrence, and this is termed biochemical recurrence. Patients with biochemical recurrence have worse survival outcomes. Radiologic localization of recurrent disease helps in directing patient management, which may vary from active surveillance to salvage radiation therapy, androgen-deprivation therapy, or other forms of systemic and local therapy. The likelihood of detecting the site of recurrence increases with higher serum PSA level. MRI provides optimal diagnostic performance for evaluation of the prostatectomy bed. Prostate-specific membrane antigen (PSMA) PET radiotracers currently approved by the U.S. Food and Drug Administration demonstrate physiologic urinary excretion, which can obscure recurrence at the vesicourethral junction. However, MRI and PSMA PET/CT have comparable diagnostic performance for evaluation of local recurrence after external-beam radiation therapy or brachytherapy. PSMA PET/CT outperforms MRI in identifying recurrence involving the lymph nodes and bones. Caveats for use of both PSMA PET/CT and MRI do exist and may cause false-positive or false-negative results. Hence, these techniques have complementary roles and should be interpreted in conjunction with each other, taking the patient history and results of any additional prior imaging studies into account. Novel PSMA agents at various stages of investigation are being developed, and preliminary data show promising results; these agents may revolutionize the landscape of prostate cancer recurrence imaging in the future. ©RSNA, 2023 Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Turkbey in this issue. The slide presentation from the RSNA Annual Meeting is available for this article.

The impact of the apparent diffusion coefficient for the early prediction of the treatment response after definitive radiotherapy in prostate cancer patients

PURPOSE

We assessed early changes in apparent diffusion coefficient (ADC) and serum prostate specific antigen (PSA) values after definitive radiotherapy (RT) without androgen deprivation treatment in low- and intermediate-risk prostate cancer (PC) patients.

MATERIALS AND METHODS

The clinical data and ADC parameters of 229 PC patients were retrospectively evaluated. Pre-treatment and post-treatment serum PSA and primary tumor ADC values were calculated. Post-treatment DW-MRI was performed median 4.1 months after completion of definitive RT. The prognostic factors predicting freedom from biochemical failure (FFBF) and progression-free survival (PFS) were analyzed using univariable and multivariable analyses.

RESULTS

With a median follow-up time of 80.8 months, the 5-year FFBF and PFS rates were 95.9% and 89.3%, respectively. Eleven patients (4.8%) had PSA relapse, with a median of 34.4 months after the completion of RT. A statistically significant difference in post-treatment ADC values was noted between patients with and without recurrence (0.94 ± 0.07 vs. 1.10 ± 0.20 × 10^-3 mm²/sec; p < 0.001). Patients with a Gleason score (GS) of 6 and low-risk disease had significantly higher post-treatment tumor ADC and PSA levels than patients with a GS of 7 and intermediate-risk disease. The 5-year FFBF rate in patients with tumor ADC ≤ 0.96 × 10^-3 mm²/sec was significantly lower than patients with tumor ADC > 0.96 × 10^-3 mm²/sec (85.5% vs. 100; p < 0.001). In the multivariable analysis, a lower ADC value, GS 4 + 3 and intermediate-risk disease were independent predictors of worse FFBF. In the multivariate analysis, a lower post-treatment ADC value and a GS of 4+3 were significant prognostic factors for a lower PFS.

CONCLUSION

These findings suggest that the post-treatment tumor ADC value could be used for early treatment response evaluation after definitive RT in PC patients.

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.

Monitoring the therapeutic efficacy of CA4P in the rabbit VX2 liver tumor using dynamic contrast-enhanced MRI

PURPOSE

The present work aims to evaluate whether dynamic contrast-enhanced magnetic resonance Imaging (DCE-MRI) can monitor non-invasively the blocking effect on microvessels of the Combretastatin-A4-phosphate (CA4P) and assess the therapeutic efficacy.

METHODS

Forty rabbits were implanted the VX2 tumors specimens. Two weeks later, serial MRI (T1 weighted image, T2 weighted image and DCE) were performed at 0 h, 4 h, 24 h, 3 d and 7 d after CA4P (10 mg/kg) or saline treatment. The parameters of DCE (Ktrans, Kep, Ve and iAUC60) of enhancement tumor portions were measured. Then all the tumor samples were stained to count microvessel density (MVD). At last, two-way repeated measures ANOVA was used to analyze the difference between and within groups. The correlation between the Ktrans, Kep, Ve, iAUC60 and MVD was analyzed by using the Pearson correlation analysis and Spearman's rank correlation.

RESULTS

The Ktrans and iAUC60 in the CA4P group were lower than the values of the control group at 4 h after treatment, which have significant differences (D-value: -0.133 min-1, 95%CI: -0.169~-0.097 min-1，F = 59.109, p < 0.001 for Ktrans; D-value: -10.533 mmol/sec, 95%CI: -17.147~-3.919 mmol/sec，F = 11.110, and p = 0.003 for iAUC60). In the CA4P group, the Ktrans and iAUC60 reached the minimum values at 4 h. There were significant differences between 4 h and other different time points of the Ktrans and iAUC60 in the treatment group (all p < 0.01). The parameters Ktrans (r = 0.532, P = 0.016 and r = 0.681, P = 0.001, respectively) and iAUC60 (r = 0.580, P = 0.007 and r = 0.568, P = 0.009, respectively) of 7 days showed correlation with MVD in both groups, while Kep and Ve did not show correlation with MVD (P > 0.05).

CONCLUSION

The blocking effect of microvessels after CA4P treatment can be evaluated by DCE-MRI, and the parameters of quantitative Ktrans and semi- quantitative iAUC60 can assess the change of the tumor angiogenesis noninvasively.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.