Diagnostic efficiency of hybrid imaging using PSMA ligands, PET/CT, PET/MRI and MRI in identifying malignant prostate lesions

Comparison of 18F-based PSMA radiotracers with [68Ga]Ga-PSMA-11 in PET/CT imaging of prostate cancer-a systematic review and meta-analysis

BACKGROUND

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) has become an increasingly established imaging modality in the staging of prostate cancer (PCa). Numerous PSMA-based tracers are currently available, however, there is a lack of consensus on the optimal radiotracer(s) for PSMA PET/CT. This study aims to investigate whether Fluorine-18 (18F)-labelled PSMA PET/CT is significantly different from Gallium-68 (68Ga) in primary diagnosis and/or secondary staging of prostate cancer following biochemical recurrence.

METHODS

A critical review of MEDLINE, EMBASE, PubMed and Web of Science databases was performed in May 2023 according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. Studies that directly compared 18F-based PSMA radiotracers and [68Ga]Ga-PSMA-11 in terms of the normal organ SUV or the lesion SUV or the detection rate were assessed. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2).

RESULTS

Twenty-four studies were analysed. [18F]DCFPyL and [18F]PSMA-1007 were the two most commonly studied 18F based PSMA tracers. [18F]JK-PSMA-7, [18F]rhPSMA-7, [18F]AlF-PSMA-11 were the new tracers evaluated in a limited number of studies. Overall, [18F]DCFPyL was observed to have a similar lesion detection rate to [68Ga]Ga-PSMA-11 with no increase in false positive rates. [18F]PSMA-1007 was found to have a greater local lesion detection rate because of its predominant hepatobiliary excretory route. However, [68Ga]Ga-PSMA-11 was observed to have a similar local lesion detection rate in studies that administer patients with furosemide prior to the scan. In addition, [18F]PSMA-1007 was found to have a significant number of benign bone uptakes.

CONCLUSIONS

[18F]DCFPyL was observed to be similar to [68Ga]Ga-PSMA-11. [18F]PSMA-1007 was observed to be less preferrable to [68Ga]Ga-PSMA-11 due to its high benign bone uptakes. Overall, there was not enough evidence in differentiating the radiotracers based on their clinical impacts.

Metabolic Imaging for Radiation Therapy Treatment Planning: The Role of Hybrid PET/MR Imaging

The use of hybrid PET/MR imaging for radiotherapy treatment planning has the potential to reduce tumor and organ displacements caused by different scan times and setup changes. Although with mixed results mainly due to single-center studies with small sample size, PET/MR imaging could provide better target delineation, especially by reducing coregistration discrepancies on computed tomography simulation scan and offering better soft tissue contrast. The main limitation to drive stronger conclusions is due to the relatively low availability of hybrid PET/MR imaging systems, mainly limited to large academic centers.

Comparing the Detection Performance Between Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen PET/CT in Patients With Localized Prostate Cancer: A Systematic Review and Meta-analysis

PURPOSE

Multiparametric MRI (mpMRI) has been promoted as an auxiliary diagnostic tool for prostate biopsy. However, prostate-specific membrane antigen (PSMA) including 68 Ga-PSMA-11, 18 F-DCFPyL, and 18 F-PSMA-1007 applied PET/CT imaging was an emerging diagnostic tool in prostate cancer patients for staging or posttreatment follow-up, even early detecting. Many studies have used PSMA PET for comparison with mpMRI to test the diagnostic ability for early prostate cancer. Unfortunately, these studies have shown conflicting results. This meta-analysis aimed to compare the differences in diagnostic performance between PSMA PET and mpMRI for detecting and T staging localized prostatic tumors.

METHODS

This meta-analysis involved a systematic literature search of PubMed/MEDLINE and Cochrane Library databases. The pooling sensitivity and specificity of PSMA and mpMRI verified by pathological analysis were calculated and used to compare the differences between the 2 imaging tools.

RESULTS

Overall, 39 studies were included (3630 patients in total) from 2016 to 2022 in the current meta-analysis and found that the pooling sensitivity values for localized prostatic tumors and T staging T3a and T3b of PSMA PET were 0.84 (95% confidence interval [CI], 0.83-0.86), 0.61 (95% CI, 0.39-0.79), and 0.62 (95% CI, 0.46-0.76), respectively, whereas those of mpMRI were found to be 0.84 (95% 0.78-0.89), 0.67 (95% CI, 0.52-0.80), and 0.60 (95% CI, 0.45-0.73), respectively, without significant differences ( P > 0.05). However, in a subgroup analysis of radiotracer, the pooling sensitivity of 18 F-DCFPyL PET was higher than mpMRI (relative risk, 1.10; 95% CI, 1.03-1.17; P < 0.01).

CONCLUSIONS

This meta-analysis found that whereas 18 F-DCFPyL PET was superior to mpMRI at detecting localized prostatic tumors, the detection performance of PSMA PET for localized prostatic tumors and T staging was comparable to that of mpMRI.

Feasibility of biology-guided radiotherapy using PSMA-PET to boost to dominant intraprostatic tumour

•

Biology-guided radiation therapy (BGRT) uses PET imaging for online image guidance.

•

PSMA PET uptake is abundant in the dominant intraprostatic lesion (DIL).

•

BgRT boost to PSMA-avid subvolume in the prostate region may be feasible.

•

Suitable targets for BgRT were identified in the ProPSMA clinical trial.

Background

Methods

Results

Conclusions

Time point-independent tumor positivity of 68Ga-PSMA-PET/CT pre- and post-biopsy in high-risk prostate cancer

OBJECTIVE

Prostate-specific membrane antigen (PSMA)-PET/CT imaging has gained increasing clinical importance for the detection and staging of high-risk primary prostate cancer (PCa). However, it is unclear whether the routine practice of prostate biopsy obscures the image finding of PSMA-PET/CT. This study aimed to compare the tumor positivity rate of PSMA-PET/CT performed pre- (PSMA-PET/CT_pre) and post-biopsy (PSMA-PET/CT_post) in high-risk PCa patients.

PATIENTS AND METHODS

We matched 58 PSMA-PET/CT_post with 58 PSMA-PET/CT_pre studies for primary detection of high-risk PCa according to clinical characteristics. Three subgroups of PSMA-PET/CT_post were defined by the intervals after biopsy (≤ 1 week, 1 ~ 2 weeks, and 2 ~ 5 weeks). Tumor positivity rates were determined, and SUVmax of primary tumors were compared separately for the two main groups and the related subgroups. Malignant prostate tissues from 20 of these patients were examined by immunohistochemical analysis of PSMA. In addition, the values of PSMA-PET/CT_pre and PSMA-PET/CT_post in assessing seminal vesicle invasion (SVI) were evaluated in patients who underwent radical prostatectomy.

RESULTS

All the primary tumors were positive on PSMA-PET/CT_post and PSMA-PET/CT_pre imaging, resulting in a patient-based positivity rates of 100% (58/58) in both groups. All examined IHC results (20/20) confirmed the high-level expression of PSMA. SUVmax of primary tumors did not differ between the two main groups (16.1, IQR 9.8-26.6 vs. 16.5, IQR 11.0-26.7, p > 0.05). Subgroup analysis of PSMA-PET/CT_post (≤ 1 week, 1 ~ 2 weeks, and 2 ~ 5 weeks) also showed no significant difference in tumor SUVmax (15.8, IQR 9.5-22.2; 17.8, IQR 9.8-29.2; and 15.4, IQR 10.1-30.3. p > 0.05). PSMA-PET/CT_post and PSMA-PET/CT_pre exhibited similar value in SVI detection as well.

CONCLUSIONS

The tumor positivity rate was consistently high for PSMA-PET/CT pre- and post-biopsy. A prior biopsy does not seem to affect the tumor positivity rate of PSMA-PET/CT in high-risk PCa.

Applications of artificial intelligence in prostate cancer imaging

PURPOSE OF REVIEW

The purpose of this review was to identify the most recent lines of research focusing on the application of artificial intelligence (AI) in the diagnosis and staging of prostate cancer (PCa) with imaging.

RECENT FINDINGS

The majority of studies focused on the improvement in the interpretation of bi-parametric and multiparametric magnetic resonance imaging, and in the planning of image guided biopsy. These initial studies showed that AI methods based on convolutional neural networks could achieve a diagnostic performance close to that of radiologists. In addition, these methods could improve segmentation and reduce inter-reader variability. Methods based on both clinical and imaging findings could help in the identification of high-grade PCa and more aggressive disease, thus guiding treatment decisions. Though these initial results are promising, only few studies addressed the repeatability and reproducibility of the investigated AI tools. Further, large-scale validation studies are missing and no diagnostic phase III or higher studies proving improved outcomes regarding clinical decision making have been conducted.

SUMMARY

AI techniques have the potential to significantly improve and simplify diagnosis, risk stratification and staging of PCa. Larger studies with a focus on quality standards are needed to allow a widespread introduction of AI in clinical practice.