Next Article in Journal
Clinical Observations of Psychiatric and Sexual Outcomes in Patients with Trazodone-Associated Ischemic Priapism
Previous Article in Journal
The Impact of Inspiratory Muscle Training on Diaphragm Thickness in Healthy Adults: A Systematic Review and Meta-Regression
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Medicina
Volume 62
Issue 3
10.3390/medicina62030610
medicina-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Integrating Multiparametric MRI and PSMA PET Imaging in Prostate Cancer: Toward a Unified Diagnostic and Risk-Stratification Paradigm

by
Rosa Alba Pugliesi
1,*,
Roberto Cannella
1,
Karim Ben Mansour
2,
Daniele Di Biagio
3 and
Pierpaolo Alongi
1
1
Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Via del Vespro 129, 90127 Palermo, Italy
2
Department of Radiology, Hôpital de Morges, Chemin du Crêt 2, 1110 Morges, Switzerland
3
Nuclear Medicine Centre, San Pietro Fatebenefratelli Hospital—Express Diagnostics, Via Cassia 600, 00189 Rome, Italy
*
Author to whom correspondence should be addressed.
Medicina 2026, 62(3), 610; https://doi.org/10.3390/medicina62030610
Submission received: 28 January 2026 / Revised: 27 February 2026 / Accepted: 13 March 2026 / Published: 23 March 2026
(This article belongs to the Special Issue Advances in Use of PET-CT Imaging in Disease Diagnosis)
Browse Figures
Versions Notes

Abstract

Prostate cancer represents a highly prevalent malignancy affecting men globally, necessitating precise staging and risk stratification for effective patient management. Multiparametric magnetic resonance imaging (mpMRI) and prostate-specific membrane antigen positron emission tomography (PSMA PET) have individually revolutionized the diagnosis and management of prostate cancer. Recent developments emphasize the integration of these imaging modalities to improve detection capabilities, inform therapeutic interventions, and facilitate personalized management. This narrative article reviews existing literature on the clinical utilization of mpMRI and PSMA PET in prostate cancer. Key areas encompass initial diagnosis, both local and systemic staging, detection of biochemical recurrence, and their influence in treatment strategies. The integration of mpMRI and PSMA PET offers complementary insights, with mpMRI demonstrating superior capability in local tumor characterization and PSMA PET enhancing the detection of nodal and distant metastases. Quantitative imaging biomarkers, including apparent diffusion coefficient (ADC) and standardized uptake values (SUV), have the potential to improve risk stratification and inform personalized treatment strategies. Hybrid imaging techniques may improve diagnostic accuracy and guide decisions regarding surgery, radiotherapy, and systemic treatment. The integration of mpMRI and PSMA PET allows a potentially transformative advancement in the realm of precision imaging for prostate cancer. This integrated approach can improve diagnostic accuracy, better define disease extent, and support personalized management strategies.

1. Introduction

Prostate cancer is one of the most frequently diagnosed cancers among males worldwide. In 2022 there were an estimated 1,466,680 new cases of prostate cancer globally and about 396,792 deaths attributable to the disease, making it the second most commonly diagnosed cancer in men and the fifth leading cause of cancer death worldwide [1,2,3]. Based on recent international cancer statistics, prostate cancer is responsible for over 1.4 million new cases each year, with significant regional differences in incidence and prognosis [4,5]. Although many patients are diagnosed with indolent disease, a substantial proportion present with or develop clinically aggressive cancer, highlighting the heterogeneity of prostate cancer biology [6]. This variability requires precise risk stratification to effectively manage the competing risks of overtreatment and undertreatment. Current management strategies are progressively dependent on imaging-based evaluations to guide diagnosis, staging, and personalized treatment [7].
Standard diagnostic approaches for prostate cancer typically involve prostate-specific antigen (PSA) testing, digital rectal examination, systematic transrectal ultrasound-guided biopsy, and imaging techniques such as computed tomography and bone scintigraphy [8]. However, these exams have inherent limitations such as biopsy sampling error that may underestimate tumor grade or overlook clinically significant lesions [9]. Furthermore, conventional imaging demonstrates limited sensitivity in detecting early osseous metastases, thereby restricting its effectiveness for precise staging [10]. These limitations have prompted the implementation of advanced imaging modalities that offer improved anatomic localization and detailed biological characterization of disease [11].
Progress in prostate imaging over the last decade has transformed the diagnostic landscape, with multiparametric MRI (mpMRI) and prostate-specific membrane antigen positron emission tomography (PSMA PET) being the main imaging modalities for the diagnosis and staging [12]. mpMRI has demonstrated high diagnostic performance in intraprostatic tumor detection and local staging relative to conventional imaging techniques, whereas PSMA PET has demonstrated significantly greater sensitivity for identifying nodal and distant metastatic disease [13]. Increasing evidence suggests that these techniques provide complementary information across clinical scenarios.
Importantly, current standard staging pathways generally apply mpMRI for local assessment and reserve PSMA PET primarily for high-risk staging or biochemical recurrence [14]. In contrast, the integrated paradigm discussed in this review proposes coordinated interpretation of both modalities across defined clinical scenarios to refine risk classification and therapeutic planning. This conceptual distinction between sequential use and structured integration underpins the analytical framework of the present review.
This narrative article reviews existing literature on mpMRI and PSMA PET in prostate cancer and critically evaluates their complementary integration within contemporary risk stratification models.
Although designed as a narrative review, a structured literature search was performed to enhance transparency. PubMed/MEDLINE, Embase, and Web of Science were searched for studies published between January 2015 and January 2026 using predefined keywords (Supplementary Table S1). Priority was given to randomized trials, prospective multicenter studies, meta-analyses, and guideline-defining publications. Exploratory single-center studies were included when addressing emerging topics such as radiomics or artificial intelligence. Non-English articles, case reports, and studies lacking histopathologic or clinical validation were excluded.

2. Multiparametric MRI (mpMRI) in Prostate Cancer

2.1. Technical Considerations

Multiparametric MRI combines high-resolution T2-weighted imaging with functional techniques, such as diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging, to characterize prostate lesions at both the anatomical and cellular levels [15]. Among these sequences, DWI and the apparent diffusion coefficient (ADC) are the most relevant tools, as decreased ADC values are associated with increased tumor cellularity and a higher histopathologic grade [16]. Standardized interpretation is achieved through structured reporting systems such as the PI-RADS that include lesion morphology, diffusion properties, and presence of enhancement, allowing for consistent lesion evaluation and risk stratification. These technological advancements have established multiparametric MRI (mpMRI) as an integral component of contemporary prostate cancer imaging.

2.2. Clinical Applications of mpMRI

mpMRI is essential in the detection, localization, and characterization of primary prostate cancer [17]. Prospective studies and meta-analyses have shown that mpMRI-guided biopsy improves the detection of clinically significant prostate cancer while decreasing unnecessary biopsies and the overdiagnosis of low-risk conditions [18]. Beyond diagnosis, mpMRI remains the imaging modality of choice for local staging, offering essential insights into extracapsular extension, seminal vesicle invasion, and the tumor’s proximity to neurovascular structures [19]. These characteristics directly impact surgical planning, the delineation of radiotherapy targets, and eligibility criteria for focal therapies or active surveillance strategies [18].
Despite the high diagnostic performance of mpMRI, histopathologic confirmation through biopsy remains the reference standard for prostate cancer diagnosis and grading [20]. Imaging findings, whether derived from mpMRI, PSMA PET, or integrated approaches, must therefore be interpreted in conjunction with targeted or systematic biopsy results to establish definitive ground truth.

2.3. Limitations of mpMRI

Although it is well-established, false-negative results may arise in cases involving small-volume tumors, low-grade malignancies, or lesions exhibiting limited diffusion restriction [21]. Additionally, diagnostic accuracy may be diminished within the transition zone [22]. Interobserver variability continues to be a concern, especially outside high-volume centers, and image quality is affected by scanner technology and acquisition parameters [21]. Recent comparative studies indicate that certain biologically significant tumors may display minimal conspicuity on mpMRI while showing pronounced uptake on PSMA PET, emphasizing the importance of employing complementary imaging modalities rather than depending solely on a single technique [11].

3. PSMA PET Imaging in Prostate Cancer

3.1. Technical Overview

Prostate-specific membrane antigen (PSMA) PET imaging capitalizes on the significant overexpression of PSMA on prostate cancer cells, particularly in high-grade and metastatic disease. In clinical practice, PSMA PET is most frequently conducted using hybrid PET/CT or PET/MRI systems with small-molecule PSMA-targeted radioligands labeled with either 68Ga (e.g., 68Ga-PSMA-11) or 18F (e.g., 18F-DCFPyL/piflufolastat, 18F-rhPSMA-7.3/flotufolastat, 18F-PSMA-1007). Local availability, operational considerations, and tracer-specific biodistribution characteristics are the primary factors that influence the selection of a tracer [23,24,25,26].
Overall, PSMA PET tracers demonstrate broadly comparable diagnostic performance; therefore, tracer selection is primarily driven by logistical factors and known biodistribution-related pitfalls rather than consistent differences in diagnostic accuracy [22,27,28]. While 68Ga-based tracers are widely accessible, 18F-labeled tracers offer superior spatial resolution [27]. In addition, 18F-PSMA-1007 is characterized by reduced urinary excretion, which may improve evaluation of the prostate and prostate bed [29]. Among 68Ga tracers, 68Ga-PSMA-11 remains the most extensively validated tracer and benefits from on-site generator-based production; however, its short physical half-life and limited generator yield may constrain patient throughput and scheduling flexibility [23,30]. Following intravenous administration, whole-body imaging with 68Ga-PSMA-11 is typically initiated approximately 50–70 min post-injection, with delayed pelvic acquisitions performed selectively to improve lesion conspicuity [31,32]. In comparison, 18F-labeled PSMA tracers provide greater distribution efficiency and scheduling flexibility due to centralized cyclotron production and a longer half-life, as well as improved physical imaging properties. When identical targeting vectors are employed, 18F-PSMA-11 has demonstrated non-inferiority to 68Ga-PSMA-11 in a prospective randomized crossover trial [24,33]. Among available 18F agents, 18F-DCFPyL (piflufolastat) is supported by robust phase III evidence, particularly in the setting of biochemical recurrence. Conversely, 18F-PSMA-1007 may facilitate improved assessment of the pelvis and prostate bed owing to low urinary activity but is associated with interpretation challenges, including nonspecific uptake in benign bone lesions [34,35].
Hybrid PET/MRI may be preferred when superior soft-tissue contrast is required for precise local tumor localization and evaluation of extracapsular extension or seminal vesicle invasion, whereas PET/CT remains the most widely utilized modality for whole-body staging [36,37,38,39].
Image reconstruction is typically performed using iterative algorithms, such as ordered-subset expectation maximization (OSEM), with increasing adoption of regularized reconstruction techniques (e.g., block-sequential regularized expectation maximization, BSREM), particularly on digital time-of-flight (TOF) systems, to reduce image noise while preserving lesion detectability and quantitative accuracy [32]. Quantitative metrics, including standardized uptake values (SUVs) and tumor-to-background ratios, provide semi-quantitative measures of tracer uptake and have been associated with tumor burden and biological aggressiveness [39]. However, the establishment of standardized quantitative thresholds remains an area of ongoing investigation [40].

3.2. Clinical Applications of PSMA PET

PSMA PET has shown improved diagnostic accuracy relative to conventional imaging modalities in identifying nodal and distant metastases [25]. During the initial staging procedure, PSMA PET has demonstrated clinically meaningful diagnostic accuracy for primary staging and biochemical recurrence, including superiority over conventional imaging for detecting nodal, even when they are smaller than one centimetre, and distant metastases in high-risk disease [13,40,41,42]. Its significance is especially recognized in cases of biochemical recurrence, where PSMA PET effectively detects disease at low PSA levels, often leading to alterations in clinical management [43]. Prospective evidence shows high positive predictive value and PSA-dependent detection, supporting its use to localize disease when salvage strategies are being considered [39,44,45]. Head-to-head comparisons indicate that PSMA PET generally outperforms conventional imaging and can outperform other PET tracers (e.g., fluciclovine, choline) in clinically relevant recurrence settings, informing tracer choice when PET is pursued for management decisions [46,47,48]. Current studies have demonstrated that PSMA PET findings commonly result in modifications to treatment strategies, such as incorporating metastasis-directed therapy, adjusting radiotherapy fields, or initiating systemic therapy [49,50]. Consequently, PSMA PET has become a fundamental component in contemporary protocols for the staging and restaging of prostate cancer. For reporting, standardized interpretation frameworks (e.g., PROMISE miTNM, PSMA-RADS, and EANM-aligned procedure/reporting guidance) are increasingly used to improve reproducibility and multidisciplinary communication [51].

3.3. Limitations of PSMA PET

Despite its high sensitivity, physiological uptake in organs such as the salivary glands, kidneys, liver, and sympathetic ganglia may result in false-positive findings and confound image interpretation [52]. Furthermore, certain prostate malignancies, particularly those that are low-grade or neuroendocrine-differentiated, may exhibit minimal or no PSMA expression, which can lead to false-negative imaging results [53]. The detection of diseases that involve very small volumes continues to present significant challenges, and partial-volume effects may impede precise quantification [53].
The major unresolved limitations of clinical PSMA PET are as follows: (1) false positives, particularly isolated or equivocal bone uptake due to non-prostatic PSMA expression/benign causes, and (2) limited sensitivity for micrometastatic disease below PET resolution, particularly in pelvic lymph nodes, so a negative scan cannot exclude microscopic spread [27,40,54].

4. Integration of mpMRI and PSMA PET: Toward a Unified Diagnostic and Risk-Stratification Paradigm

In clinical practice, the integrated paradigm is best conceptualized across specific clinical scenarios: (1) primary diagnosis in biopsy-naïve patients, (2) initial staging in intermediate–high-risk disease, (3) biochemical recurrence, and (4) treatment planning for surgery or radiotherapy. Framing integration within these distinct scenarios allows clearer differentiation of evidence strength and clinical utility.
The integrated use of mpMRI and PSMA PET/CT takes advantage of the complementary strengths of high-resolution local anatomic imaging and whole-body molecular staging to improve the detection and characterization of intraprostatic disease, nodal spread, and distant metastases in intermediate–high-risk prostate cancer patients [27,52,55,56]. Meta-analyses and comparative studies have demonstrated that PSMA PET/CT generally shows higher pooled sensitivity than mpMRI for lymph node metastasis detection (74% vs. 45%) with similarly high specificity (96% vs. 92%) when pelvic lymph node dissection is used as the reference standard [57]. Moreover, other pooled analyses in intermediate–high-risk cohorts report that 68Ga-PSMA PET/CT achieves sensitivities in the range of approximately 65–74% and specificities of 94–97% for nodal staging, compared with lower or variable sensitivities for mpMRI [58]. This evidence suggests that combining mpMRI and PSMA PET/CT can enhance overall diagnostic performance and provide greater confidence in staging decisions than either modality alone.
By distinguishing between localized and systemic prostate cancer, this boosts diagnostic precision, refines risk stratification, and more effectively informs treatment decisions [59]. This comprehensive approach is consistent with the emergence of radiomics-based models that utilize multimodal imaging to characterize tumor phenotype and aggressiveness in a manner that surpasses traditional staging systems [60] (Table 1).
mpMRI and PSMA PET offer unique and complementary information [61]. mpMRI is capable of accurately detect prostate lesions, characterize lesions, and evaluate extracapsular extension or seminal vesicle invasion, thereby assisting in the planning of local treatment [60]. In the case of the primary tumor, mpMRI remains the reference standard for local staging (e.g., assessment of extracapsular extension or ECE and seminal vesicle invasion or SVI) [62]. However, PSMA PET can provide additional value in tumor localization and risk stratification, particularly when mpMRI is ambiguous [63]. This supports combined interpretation and, when feasible, PET/MRI strategies [27,36,46,64]. PSMA PET enables thorough whole-body staging through tumor-specific molecular targeting, allowing for the detection of nodal and distant metastases [24]. For pelvic nodal staging, PSMA PET/CT offers higher accuracy than conventional imaging but still misses micrometastases, so its main advantage is identifying clinically actionable N disease beyond CT/MRI size criteria rather than replacing surgical nodal staging when indicated [39,46,52,65].
For distant metastases, PSMA PET/CT improves detection versus conventional imaging and can upstage patients with otherwise “localized” disease, enabling more appropriate systemic and/or metastasis-directed management selection [46,66]. The complementary strengths of mpMRI and PSMA-PET are summarized in Table 2.
Inconsistent results are often encountered due to differences in sensitivity to tumor volume, grade, and biological features. Integrated imaging improves local staging and surgical risk assessment by reducing ambiguous interpretations and elevating staging accuracy [62]. This is achieved by using multiparametric MRI to identify the primary intraprostatic lesion and PSMA PET to detect additional capsular-adjacent PET-avid foci (Figure 1).
It is indispensable to recognize that the discrepancy between the findings of mpMRI and PSMA PET should not be read as a mere limitation of either modality, but rather as an indication of the heterogeneity of the underlying tumor [65]. In contrast, certain MRI-conspicuous tumors may exhibit low PSMA uptake as a result of variable target expression or dedifferentiation, while lesions with low cellular density or limited diffusion restriction may express high PSMA [67]. It is imperative to acknowledge these biological distinctions in order to prevent misinterpretation and to substantiate the case for the use of combined imaging over sequential or competitive methods [68].
As illustrated in Figure 2, the schematic comparison clarifies that the proposed paradigm does not replace established diagnostic standards but seeks to harmonize anatomical and molecular data earlier in the decision process. The integration framework emphasizes structured interpretation rather than parallel, uncoordinated test utilization.
Integrated mpMRI and PSMA PET enable the reclassification of clinically significant risks across diagnostic, recurrent, and treatment-planning settings (Table 3).
In patients without prior biopsy, integrated imaging improves the identification of clinically significant intraprostatic pathology while efficiently ruling out occult metastases, thereby reducing the risk of understaging [71]. In recurrence, multiparametric MRI allow to confirm PSMA PET findings by demonstrating the presence of tumor recurrence with diffusion restriction (Figure 3), thereby providing direct guidance for treatment planning.
In patients with intermediate- and high-risk disease, PSMA PET frequently identifies occult nodal involvement, leading to upstaging and adjustments in surgical or radiotherapy approaches [65]. During biochemical recurrence, integrated imaging improves the capacity to differentiate between local and metastatic disease, thereby informing decisions related to salvage or systemic treatment strategies [61].
Importantly, while integrated imaging improves staging confidence, it does not yet constitute a validated, outcome-driven unified risk-stratification system. Prospective randomized evidence demonstrating survival benefit or long-term outcome modification based specifically on combined mpMRI and PSMA PET remains limited [69]. Trials such as proPSMA [13] have established the superiority of PSMA PET over conventional imaging for staging accuracy, yet equivalent high-level trials directly testing combined mpMRI–PSMA paradigms are still lacking. Therefore, integration should currently be regarded as a complementary strategy rather than a fully established replacement for existing staging frameworks.
Cost-effectiveness analyses [72,73] suggest potential downstream savings through improved staging accuracy; however, real-world accessibility, radiotracer availability, infrastructure requirements, and reimbursement policies remain substantial barriers in many healthcare systems. These considerations temper the immediate generalizability of integrated imaging approaches.

5. Impact on Clinical Management

Accurate preoperative localization and staging are essential for achieving optimal surgical outcomes in prostate cancer [74,75]. New evidence suggests that the inclusion of PSMA PET, particularly in intermediate- and high-risk patients, can elevate surgical planning by detecting occult nodal disease that is not detected on MRI or conventional imaging [76,77]. In the post-prostatectomy setting, the combination of mpMRI and PSMA PET interpretation has also been demonstrated to improve the localization of local recurrence, which has the potential to contribute to salvage surgery or targeted interventions [78].
In order to optimize tumor control while minimizing adverse effects, radiotherapy necessitates precise target delineation and risk-adapted dose escalation. mpMRI provides high-resolution anatomical detail for defining dominant intraprostatic lesions, which has enabled focal boost strategies within the prostate gland [79]. PSMA PET complements this approach by identifying involved lymph nodes and distant metastases, frequently altering radiation fields and treatment intent [80]. Changes in radiotherapy planning, such as expanded nodal coverage or stereotactic treatment of oligometastatic disease, have been associated with integrated imaging approaches, thereby supporting a more personalized radiation strategy [70]. This has facilitated the prompt identification of individuals who could benefit from systemic medications, like androgen deprivation therapy or innovative androgen receptor-targeted agents [81]. Upon interpretation in conjunction with mpMRI, PSMA PET boost the ability to differentiate between localized and systemic disease, thereby facilitating the informed escalation or deescalation of systemic therapy and bolstering contemporary strategies, such as metastasis-directed treatment, within evolving therapeutic paradigms [82]. The link between tumor aggressiveness and clinical outcomes, as shown by quantitative biomarkers from mpMRI (e.g., ADC) and PSMA PET (e.g., SUV), suggests refined risk classification [83].
Combining imaging to characterize disease extent and biology may reduce overtreatment of indolent disorders and help intensify aggressive cancer treatment [84]. Integrated imaging may enable advanced, patient-specific care regimens, although more validation is needed before widespread clinical use [85].

6. Challenges and Future Directions

The absence of standardized acquisition and interpretation protocols is a substantial impediment to the widespread clinical implementation of integrated mpMRI and PSMA PET [86]. Although there is still a significant amount of variation between centers and readers, PI-RADS has improved the consistency of mpMRI reporting [87]. The necessity for standardized composite imaging methods and reporting platforms to ensure reproducibility and facilitate multicenter research is underscored by the fact that PSMA PET interpretation criteria and quantitative thresholds vary among radiotracers and institutions [88]. The EANM E-PSMA recommendations for acquisition and interpretation, PROMISE v2 with the 5-point PRIMARY score for local disease characterization and prognostic stratification, and PSMA-RADS for lesion-level likelihood classification and handling of equivocal findings are all part of the current frameworks for standardizing integrated reporting and multidisciplinary communication [50,89,90].
Despite promising prospective and retrospective findings, evidence remains limited, largely from small or single-center studies, underscoring the need for multicenter trials assessing accuracy and patient-centered outcomes [91].
Emerging total-body/Long Axial Field-of-View (LAFOV) Total-Body PET/CT systems, due to their significantly heightened sensitivity, may further augment PSMA PET/CT for primary tumor evaluation and improve the detection of very small-volume (micrometastatic) nodal disease, potentially alleviating (though not completely resolving) the acknowledged sensitivity deficiency of current PSMA PET for pelvic lymph node micrometastases [12,38,50].
Advanced analytical methodologies, encompassing radiomics, machine learning, and artificial intelligence, are progressively being investigated to amalgamate multiparametric imaging data [92]. Preliminary research indicates that the integration of quantitative mpMRI and PSMA PET characteristics may expand predictive modeling for tumor aggressiveness and therapeutic response [93]. Nevertheless, these methods are experimental and require rigorous validation, homogeneous feature extraction, and explicit model development before clinical use [94]. Theranostic potential is another mpMRI/PSMA PET imaging use. PSMA PET can identify patients with sufficient target expression and exclude those with PSMA-negative or heterogeneous illness utilizing PSMA-targeted radioligand treatment, such as 177Lu-PSMA [22]. mpMRI can detect tumor heterogeneity by revealing clinically significant but non-PSMA-avid intraprostatic components and local tumor extent. PSMA-based theranostic patient selection, combined local and systemic therapy selection, and individualized treatment sequencing can be optimized by integrated imaging [95].
Finally, cost, availability, and access still prevent broad use of advanced imaging. Due to infrastructural and radiotracer requirements, PSMA PET is limited in resource-constrained situations [96]. Cost-effectiveness assessments that account cascade effects on treatment choices and outcomes are needed to deploy integrated imaging solutions in healthcare systems [68,97].
Beyond imaging, integration with genomics, radiogenomics, and other omics-based biomarkers may facilitate more robust and generalizable risk stratification [98]. Preliminary radiogenomic studies suggest correlations between imaging phenotypes and molecular alterations, including PTEN loss and genomic risk classifiers [99]. Such integrative approaches may ultimately bridge imaging phenotype with tumor biology, supporting standardized and biologically grounded risk models. These approaches remain exploratory and should not yet be interpreted as validated clinical decision tools [53].

7. Artificial Intelligence and Advanced Computational Approaches

Interobserver variability, lesion conspicuity differences, and discordance between mpMRI and PSMA PET interpretations remain important limitations [100]. Emerging AI-based approaches may help mitigate these challenges by integrating multiparametric imaging features into reproducible predictive models. Radiomics-based analyses combining ADC metrics and PSMA uptake parameters have demonstrated potential for improved lesion classification and aggressiveness prediction [101]. Deep learning frameworks trained on multimodal imaging datasets may further enhance automated lesion detection, segmentation, and staging accuracy [102].
Nevertheless, AI-driven models remain largely investigational as challenges include small training datasets, lack of harmonized imaging acquisition protocols, variability in feature extraction pipelines, and limited external validation [103]. Before clinical implementation, standardized reporting frameworks and prospective multicenter validation are required.

8. Conclusions

Integrating mpMRI with PSMA PET can improve prostate cancer imaging and treatment. PSMA PET focuses on nodal, distal, and early recurrence. In contrast, mpMRI can precisely characterize local tumors, evaluate extracapsular expansion, and guide targeted biopsies. This integrated technique could improve surgical planning, radiation targeting, and systemic therapy by accurately identifying tumor load. Quantitative biomarkers from both modalities enable precision medicine and reduce over- or undertreatment by assessing risk individually. Standardizing imaging procedures, validating findings through prospective studies, and integrating imaging with molecular and genetic markers will improve individualized therapeutic regimens. The combination of mpMRI with PSMA PET revolutionizes precision imaging, improving diagnostic accuracy, therapeutic choices, and patient management.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/medicina62030610/s1, Supplementary Table S1. Database-Specific Search Strategies.

Author Contributions

R.A.P. conceptualised this narrative article. R.C. and K.B.M. contributed to the literature review and data interpretation. D.D.B. was responsible for the visualisation and figure preparation. P.A. supervised the work and contributed to critical revision of the manuscript. R.A.P. drafted the original manuscript, and all authors reviewed, edited, and approved the final version of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This review received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mallah, H.; Diabasana, Z.; Soultani, S.; Idoux-Gillet, Y.; Massfelder, T. Prostate Cancer: A Journey Through Its History and Recent Developments. Cancers 2025, 17, 194. [Google Scholar] [CrossRef]
  2. Raychaudhuri, R.; Lin, D.W.; Montgomery, R.B. Prostate cancer: A review. JAMA 2025, 333, 1433. [Google Scholar] [CrossRef]
  3. McDowell, S. Cancer in Men: Prostate Cancer Is #1 for 118 Countries Globally. American Cancer Society. Available online: https://www.cancer.org/research/acs-research-news/prostate-cancer-is-number-1-for-118-countries-worldwide.html (accessed on 27 September 2024).
  4. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  5. Bray, F.; Laversanne, M.; Sung, H.; Ferlay, J.; Siegel, R.L.; Soerjomataram, I.; Jemal, A. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2024, 74, 229–263. [Google Scholar] [CrossRef] [PubMed]
  6. Kania, E.; Janica, M.; Nesterowicz, M.; Modzelewski, W.; Cybulski, M.; Janica, J. Advances and Challenges in Prostate Cancer Diagnosis: A Comprehensive Review. Cancers 2025, 17, 2137. [Google Scholar] [CrossRef] [PubMed]
  7. Siegel, R.L.; Giaquinto, A.N.; Jemal, A. Cancer statistics, 2024. CA Cancer J. Clin. 2024, 74, 12–49, Erratum in CA Cancer J. Clin. 2024, 74, 203. https://doi.org/10.3322/caac.21830. PMID: 38230766. [Google Scholar] [CrossRef]
  8. Ayyad, S.M.; Abdel-Hamid, N.B.; Ali, H.A.; Labib, L.M. Multimodality imaging in prostate cancer diagnosis using artificial intelligence: Basic concepts and current state-of-the-art. Multimed. Tools Appl. 2025, 84, 42649–42678. [Google Scholar] [CrossRef]
  9. Kasivisvanathan, V.; Rannikko, A.S.; Borghi, M.; Panebianco, V.; Mynderse, L.A.; Vaarala, M.H.; Briganti, A.; Budäus, L.; Hellawell, G.; Hindley, R.G.; et al. MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis. N. Engl. J. Med. 2018, 378, 1767–1777. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  10. Combes, A.D.; Palma, C.A.; Calopedos, R.; Wen, L.; Woo, H.; Fulham, M.; Leslie, S. PSMA PET-CT in the Diagnosis and Staging of Prostate Cancer. Diagnostics 2022, 12, 2594. [Google Scholar] [CrossRef]
  11. Moore, C.M.; Giganti, F.; Albertsen, P.; Allen, C.; Bangma, C.; Briganti, A.; Carroll, P.; Haider, M.; Kasivisvanathan, V.; Kirkham, A.; et al. Reporting Magnetic Resonance Imaging in Men on Active Surveillance for Prostate Cancer: The PRECISE Recommendations-A Report of a European School of Oncology Task Force. Eur. Urol. 2017, 71, 648–655. [Google Scholar] [CrossRef] [PubMed]
  12. Alongi, P.; Morea, S.; Cannella, R.; Pugliesi, R.A.; Messina, C.; Di Biagio, D. The Rise of Total-Body PET/CT: Advancing Molecular Imaging Toward Early Cancer Detection and Potential Future Application in Prevention Healthcare. J. Clin. Med. 2026, 15, 311. [Google Scholar] [CrossRef] [PubMed]
  13. Hofman, M.S.; Lawrentschuk, N.; Francis, R.J.; Tang, C.; Vela, I.; Thomas, P.; Rutherford, N.; Martin, J.M.; Frydenberg, M.; Shakher, R.; et al. Prostate-specific membrane antigen PET-CT in patients with high-risk prostate cancer before curative-intent surgery or radiotherapy (proPSMA): A prospective, randomised, multicentre study. Lancet 2020, 395, 1208–1216. [Google Scholar] [CrossRef] [PubMed]
  14. Perera, M.; Papa, N.; Roberts, M.; Williams, M.; Udovicich, C.; Vela, I.; Christidis, D.; Bolton, D.; Hofman, M.S.; Lawrentschuk, N.; et al. Gallium-68 Prostate-specific Membrane Antigen Positron Emission Tomography in Advanced Prostate Cancer-Updated Diagnostic Utility, Sensitivity, Specificity, and Distribution of Prostate-specific Membrane Antigen-avid Lesions: A Systematic Review and Meta-analysis. Eur. Urol. 2020, 77, 403–417. [Google Scholar] [CrossRef] [PubMed]
  15. Guljaš, S.; Benšić, M.; Krivdić Dupan, Z.; Pavlović, O.; Krajina, V.; Pavoković, D.; Šmit Takač, P.; Hranić, M.; Salha, T. Dynamic Contrast Enhanced Study in Multiparametric Examination of the Prostate—Can We Make Better Use of It? Tomography 2022, 8, 1509–1521. [Google Scholar] [CrossRef]
  16. Nedelcu, A.; Oerther, B.; Benkendorff, A.; Dieckbreder, S.; Schwarzer, G.; Agrotis, G.; Schoots, I.G.; Benndorf, M. PI-RADS Version 2.1 for prostate MRI interpretation: Associations of study quality and cancer detection metrics—A systematic review and meta-analysis. Am. J. Roentgenol. 2025, 226, e2533583. [Google Scholar] [CrossRef]
  17. Woźnicki, P.; Westhoff, N.; Huber, T.; Riffel, P.; Froelich, M.F.; Gresser, E.; von Hardenberg, J.; Mühlberg, A.; Michel, M.S.; Schoenberg, S.O.; et al. Multiparametric MRI for Prostate Cancer Characterization: Combined Use of Radiomics Model with PI-RADS and Clinical Parameters. Cancers 2020, 12, 1767. [Google Scholar] [CrossRef] [PubMed]
  18. Drost, F.H.; Osses, D.; Nieboer, D.; Bangma, C.H.; Steyerberg, E.W.; Roobol, M.J.; Schoots, I.G. Prostate Magnetic Resonance Imaging, with or Without Magnetic Resonance Imaging-targeted Biopsy, and Systematic Biopsy for Detecting Prostate Cancer: A Cochrane Systematic Review and Meta-analysis. Eur. Urol. 2020, 77, 78–94. [Google Scholar] [CrossRef] [PubMed]
  19. van der Leest, M.; Cornel, E.; Israël, B.; Hendriks, R.; Padhani, A.R.; Hoogenboom, M.; Zamecnik, P.; Bakker, D.; Setiasti, A.Y.; Veltman, J.; et al. Head-to-head Comparison of Transrectal Ultrasound-guided Prostate Biopsy Versus Multiparametric Prostate Resonance Imaging with Subsequent Magnetic Resonance-guided Biopsy in Biopsy-naïve Men with Elevated Prostate-specific Antigen: A Large Prospective Multicenter Clinical Study. Eur. Urol. 2019, 75, 570–578. [Google Scholar] [CrossRef] [PubMed]
  20. Hsi, R.A.; Dinh, T.K.; Greer, M.; Bensen, C.; Mitchell, M.A.; Li, A.Y.; Stamm, A.; Henne, M. Performance of multiparametric prostate magnetic resonance imaging validated by targeted and systematic transperineal biopsies. BJUI Compass 2022, 4, 96–103. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  21. Messina, C.; Bignone, R.; Bruno, A.; Bruno, A.; Bruno, F.; Calandri, M.; Caruso, D.; Coppolino, P.; Robertis, R.; Gentili, F.; et al. Diffusion-Weighted Imaging in Oncology: An Update. Cancers 2020, 12, 1493. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  22. Park, S.Y.; Jung, D.C.; Oh, Y.T.; Cho, N.H.; Choi, Y.D.; Rha, K.H.; Hong, S.J.; Han, K. Prostate cancer: PI-RADS version 2 helps preoperatively predict clinically significant cancers. Radiology 2016, 280, 108–116. [Google Scholar] [CrossRef]
  23. Evangelista, L.; Maurer, T.; van der Poel, H.; Alongi, F.; Kunikowska, J.; Laudicella, R.; Fanti, S.; Hofman, M.S. [68Ga]Ga-PSMA Versus [18F]PSMA Positron Emission Tomography/Computed Tomography in the Staging of Primary and Recurrent Prostate Cancer. A Systematic Review of the Literature. Eur. Urol. Oncol. 2022, 5, 273–282. [Google Scholar] [CrossRef] [PubMed]
  24. Werner, R.A.; Derlin, T.; Lapa, C.; Sheikbahaei, S.; Higuchi, T.; Giesel, F.L.; Behr, S.; Drzezga, A.; Kimura, H.; Buck, A.K.; et al. 18F-Labeled, PSMA-Targeted Radiotracers: Leveraging the Advantages of Radiofluorination for Prostate Cancer Molecular Imaging. Theranostics 2020, 10, 1–16. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  25. Rahbar, K.; Giesel, F.L.; Herrmann, K.; Yun, M.; Watabe, T.; Rudolph, I.; Hoepping, A.; Maurer, T. Efficacy of [18F]PSMA-1007 PET/CT in Primary Staging of Prostate Carcinoma: A Systematic Review and Metaanalysis. J. Nucl. Med. 2026, 67, 85–91. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  26. de Kouchkovsky, I.; Aggarwal, R.; Hope, T.A. Prostate-specific membrane antigen (PSMA)-based imaging in localized and advanced prostate cancer: A narrative review. Transl. Androl. Urol. 2021, 10, 3130–3143. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  27. Alberts, I.L.; Seide, S.E.; Mingels, C.; Bohn, K.P.; Shi, K.; Zacho, H.D.; Rominger, A.; Afshar-Oromieh, A. Comparing the diagnostic performance of radiotracers in recurrent prostate cancer: A systematic review and network meta-analysis. Eur. J. Nucl. Med. Mol. Imaging 2021, 48, 2978–2989, Erratum in Eur. J. Nucl. Med. Mol. Imaging 2021, 48, 3014–3016. https://doi.org/10.1007/s00259-021-05300-8. PMID: 33550425; PMCID: PMC8263438. [Google Scholar] [CrossRef]
  28. Trabulsi, E.J.; Rumble, R.B.; Jadvar, H.; Hope, T.; Pomper, M.; Turkbey, B.; Rosenkrantz, A.B.; Verma, S.; Margolis, D.J.; Froemming, A.; et al. Optimum Imaging Strategies for Advanced Prostate Cancer: ASCO Guideline. J. Clin. Oncol. 2020, 38, 1963–1996. [Google Scholar] [CrossRef] [PubMed]
  29. Huang, S.; Ong, S.; McKenzie, D.; Mirabelli, A.; Chen, D.C.; Chengodu, T.; Murphy, D.G.; Hofman, M.S.; Lawrentschuk, N.; Perera, M. Comparison of 18F-based PSMA radiotracers with [68Ga]Ga-PSMA-11 in PET/CT imaging of prostate cancer-a systematic review and meta-analysis. Prostate Cancer Prostatic Dis. 2024, 27, 654–664. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  30. Crawford, E.D.; Koo, P.J.; Shore, N.; Slovin, S.F.; Concepcion, R.S.; Freedland, S.J.; Gomella, L.G.; Karsh, L.; Keane, T.E.; Maroni, P.; et al. A Clinician’s Guide to Next Generation Imaging in Patients with Advanced Prostate Cancer (RADAR III). J. Urol. 2019, 201, 682–692. [Google Scholar] [CrossRef] [PubMed]
  31. Park, S.Y.; Zacharias, C.; Harrison, C.; Fan, R.E.; Kunder, C.; Hatami, N.; Giesel, F.; Ghanouni, P.; Daniel, B.; Loening, A.M.; et al. Gallium 68 PSMA-11 PET/MR Imaging in Patients with Intermediate- or High-Risk Prostate Cancer. Radiology 2018, 288, 495–505. [Google Scholar] [CrossRef] [PubMed]
  32. Lindström, E.; Velikyan, I.; Regula, N.; Alhuseinalkhudhur, A.; Sundin, A.; Sörensen, J.; Lubberink, M. Regularized reconstruction of digital time-of-flight 68Ga-PSMA-11 PET/CT for the detection of recurrent disease in prostate cancer patients. Theranostics 2019, 9, 3476–3484. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  33. De Man, K.; Van Laeken, N.; Schelfhout, V.; Fendler, W.P.; Lambert, B.; Kersemans, K.; Piron, S.; Lumen, N.; Decaestecker, K.; Fonteyne, V.; et al. 18F-PSMA-11 Versus 68Ga-PSMA-11 Positron Emission Tomography/Computed Tomography for Staging and Biochemical Recurrence of Prostate Cancer: A Prospective Double-blind Randomised Cross-over Trial. Eur. Urol. 2022, 82, 501–509. [Google Scholar] [CrossRef] [PubMed]
  34. Morris, M.J.; Rowe, S.P.; Gorin, M.A.; Saperstein, L.; Pouliot, F.; Josephson, D.; Wong, J.Y.C.; Pantel, A.R.; Cho, S.Y.; Gage, K.L.; et al. Diagnostic Performance of 18F-DCFPyL-PET/CT in Men with Biochemically Recurrent Prostate Cancer: Results from the CONDOR Phase III, Multicenter Study. Clin. Cancer Res. 2021, 27, 3674–3682. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  35. Lawhn-Heath, C.; Salavati, A.; Behr, S.C.; Rowe, S.P.; Calais, J.; Fendler, W.P.; Eiber, M.; Emmett, L.; Hofman, M.S.; Hope, T.A. Prostate-specific Membrane Antigen PET in Prostate Cancer. Radiology 2021, 299, 248–260. [Google Scholar] [CrossRef] [PubMed]
  36. Grubmüller, B.; Baltzer, P.; Hartenbach, S.; D’Andrea, D.; Helbich, T.H.; Haug, A.R.; Goldner, G.M.; Wadsak, W.; Pfaff, S.; Mitterhauser, M.; et al. PSMA Ligand PET/MRI for Primary Prostate Cancer: Staging Performance and Clinical Impact. Clin. Cancer Res. 2018, 24, 6300–6307. [Google Scholar] [CrossRef] [PubMed]
  37. Muehlematter, U.J.; Burger, I.A.; Becker, A.S.; Schawkat, K.; Hötker, A.M.; Reiner, C.S.; Müller, J.; Rupp, N.J.; Rüschoff, J.H.; Eberli, D.; et al. Diagnostic Accuracy of Multiparametric MRI versus 68Ga-PSMA-11 PET/MRI for Extracapsular Extension and Seminal Vesicle Invasion in Patients with Prostate Cancer. Radiology 2019, 293, 350–358. [Google Scholar] [CrossRef] [PubMed]
  38. Hicks, R.M.; Simko, J.P.; Westphalen, A.C.; Nguyen, H.G.; Greene, K.L.; Zhang, L.; Carroll, P.R.; Hope, T.A. Diagnostic Accuracy of 68Ga-PSMA-11 PET/MRI Compared with Multiparametric MRI in the Detection of Prostate Cancer. Radiology 2018, 289, 730–737. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  39. Soeterik, T.F.W.; Heetman, J.G.; Hermsen, R.; Wever, L.; Lavalaye, J.; Vinken, M.; Bahler, C.D.; Yong, C.; Tann, M.; Kesch, C.; et al. The association of quantitative PSMA PET parameters with pathologic ISUP grade: An international multicenter analysis. Eur. J. Nucl. Med. Mol. Imaging 2024, 52, 314–325. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  40. Hirata, K.; Tamaki, N. Quantitative FDG PET Assessment for Oncology Therapy. Cancers 2021, 13, 869. [Google Scholar] [CrossRef] [PubMed]
  41. Mazzone, E.; Cannoletta, D.; Quarta, L.; Chen, D.C.; Thomson, A.; Barletta, F.; Stabile, A.; Moon, D.; Eapen, R.; Lawrentschuk, N.; et al. A Comprehensive Systematic Review and Meta-analysis of the Role of Prostate-specific Membrane Antigen Positron Emission Tomography for Prostate Cancer Diagnosis and Primary Staging before Definitive Treatment. Eur. Urol. 2025, 87, 654–671. [Google Scholar] [CrossRef] [PubMed]
  42. Mari, A.; Cadenar, A.; Giudici, S.; Cianchi, G.; Albisinni, S.; Autorino, R.; Di Maida, F.; Gandaglia, G.; Mir, M.C.; Valerio, M.; et al. A systematic review and meta-analysis to evaluate the diagnostic accuracy of PSMA PET/CT in the initial staging of prostate cancer. Prostate Cancer Prostatic Dis. 2025, 28, 56–69. [Google Scholar] [CrossRef] [PubMed]
  43. Rovera, G.; Grimaldi, S.; Oderda, M.; Marra, G.; Calleris, G.; Iorio, G.C.; Falco, M.; Grossi, C.; Passera, R.; Campidonico, G.; et al. Comparative Performance of 68Ga-PSMA-11 PET/CT and Conventional Imaging in the Primary Staging of High-Risk Prostate Cancer Patients Who Are Candidates for Radical Prostatectomy. Diagnostics 2024, 14, 1964. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  44. Wang, L.; Wang, L.; Wang, X.; Wu, D. The Evolving Role of PSMA-PET/CT in Prostate Cancer Management: An Umbrella Review of Diagnostic Restaging, Therapeutic Redirection, and Survival Impact. Curr. Oncol. Rep. 2025, 27, 774–787. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  45. Fendler, W.P.; Calais, J.; Eiber, M.; Flavell, R.R.; Mishoe, A.; Feng, F.Y.; Nguyen, H.G.; Reiter, R.E.; Rettig, M.B.; Okamoto, S.; et al. Assessment of 68Ga-PSMA-11 PET Accuracy in Localizing Recurrent Prostate Cancer: A Prospective Single-Arm Clinical Trial. JAMA Oncol. 2019, 5, 856–863. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  46. Morgan, T.M.; Boorjian, S.A.; Buyyounouski, M.K.; Chapin, B.F.; Chen, D.Y.T.; Cheng, H.H.; Chou, R.; Jacene, H.A.; Kamran, S.C.; Kim, S.K.; et al. Salvage Therapy for Prostate Cancer: AUA/ASTRO/SUO Guideline Part I: Introduction and Treatment Decision-Making at the Time of Suspected Biochemical Recurrence after Radical Prostatectomy. J. Urol. 2024, 211, 509–517. [Google Scholar] [CrossRef] [PubMed]
  47. Chow, K.M.; So, W.Z.; Lee, H.J.; Lee, A.; Yap, D.W.T.; Takwoingi, Y.; Tay, K.J.; Tuan, J.; Thang, S.P.; Lam, W.; et al. Head-to-head Comparison of the Diagnostic Accuracy of Prostate-specific Membrane Antigen Positron Emission Tomography and Conventional Imaging Modalities for Initial Staging of Intermediate- to High-risk Prostate Cancer: A Systematic Review and Meta-analysis. Eur. Urol. 2023, 84, 36–48, Erratum in Eur. Urol. 2024, 85, e60–e61. https://doi.org/10.1016/j.eururo.2023.10.016. PMID: 37032189. [Google Scholar] [CrossRef]
  48. Calais, J.; Ceci, F.; Eiber, M.; Hope, T.A.; Hofman, M.S.; Rischpler, C.; Bach-Gansmo, T.; Nanni, C.; Savir-Baruch, B.; Elashoff, D.; et al. 18F-fluciclovine PET-CT and 68Ga-PSMA-11 PET-CT in patients with early biochemical recurrence after prostatectomy: A prospective, single-centre, single-arm, comparative imaging trial. Lancet Oncol. 2019, 20, 1286–1294, Erratum in Lancet Oncol. 2019, 20, e613. https://doi.org/10.1016/S1470-2045(19)30593-5. Erratum in Lancet Oncol. 2020, 21, e304. https://doi.org/10.1016/S1470-2045(20)30279-5. PMID: 31375469; PMCID: PMC7469487. [Google Scholar] [CrossRef]
  49. Edge, R.; Picheca, L. PET Diagnostic Imaging with Prostate-Specific Membrane Antigen for Prostate Cancer: A Review of Clinical Utility, Cost-Effectiveness, Diagnostic Accuracy, and Guidelines; Canadian Agency for Drugs and Technologies in Health: Ottawa, ON, Canada, 2020. Available online: https://www.ncbi.nlm.nih.gov/books/NBK567203/ (accessed on 28 February 2026).
  50. Gomis-Sellés, E.; Maldonado, A.; Gaztañaga, M.; Vera, V.; Ajulia, O.; Sancho, G.; Siva, S.; Lopez-Campos, F.; Couñago, F. Impact of PSMA-PET/CT on Radiotherapy Decisions: Is There a Clinical Benefit? Cancers 2025, 17, 1350. [Google Scholar] [CrossRef]
  51. Emmett, L.; van Leeuwen, P.J.; Nandurkar, R.; Scheltema, M.J.; Cusick, T.; Hruby, G.; Kneebone, A.; Eade, T.; Fogarty, G.; Jagavkar, R.; et al. Treatment Outcomes from 68Ga-PSMA PET/CT-Informed Salvage Radiation Treatment in Men with Rising PSA After Radical Prostatectomy: Prognostic Value of a Negative PSMA PET. J. Nucl. Med. 2017, 58, 1972–1976. [Google Scholar] [CrossRef] [PubMed]
  52. Ceci, F.; Oprea-Lager, D.E.; Emmett, L.; Adam, J.A.; Bomanji, J.; Czernin, J.; Eiber, M.; Haberkorn, U.; Hofman, M.S.; Hope, T.A.; et al. E-PSMA: The EANM standardized reporting guidelines v1.0 for PSMA-PET. Eur. J. Pediatr. 2021, 48, 1626–1638. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  53. Hoffmann, M.A.; von Eyben, F.E.; Fischer, N.; Rosar, F.; Müller-Hübenthal, J.; Buchholz, H.G.; Wieler, H.J.; Schreckenberger, M. Comparison of [18F]PSMA-1007 with [68Ga]Ga-PSMA-11 PET/CT in Restaging of Prostate Cancer Patients with PSA Relapse. Cancers 2022, 14, 1479. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  54. Dorado, C.Q.; Ramírez, A.S.; Pérez, M.P.; Centeno, M.S.; Mici, L.P.; Güemez, C.M.; Albers Acosta, E.; Luis, G.C.; Costal, M.; Diez, P.T.; et al. Redefining Prostate Cancer Precision: Radiogenomics, Theragnostics, and AI-Driven Biomarkers. Cancers 2025, 17, 3747. [Google Scholar] [CrossRef]
  55. Ulaner, G.A.; Thomsen, B.; Bassett, J.; Torrey, R.; Cox, C.; Lin, K.; Patel, T.; Techasith, T.; Mauguen, A.; Rowe, S.P.; et al. 18F-DCFPyL PET/CT for Initially Diagnosed and Biochemically Recurrent Prostate Cancer: Prospective Trial with Pathologic Confirmation. Radiology 2022, 305, 419–428. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  56. Walz, J.; Attard, G.; Bjartell, A.; Blanchard, P.; Castro, E.; Compérat, E.; Emmett, L.; Fanti, S.; Fonteyne, V.; Foulon, S.; et al. Local and locoregional prostate cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann. Oncol. 2025, 27, 453–469. [Google Scholar] [CrossRef] [PubMed]
  57. Sharma, A.P.; Kumar, R.; Chauhan, R.; Ziauddin, S.A.; Singh, S.; Singh, H.; Devana, S.K.; Gorsi, U.; Bora, G.S.; Mavuduru, R.S.; et al. Accuracy of combined multi-parametric MRI and PSMA PET-CT in diagnosing localized prostate cancer: Newer horizons for a biopsy-free pathway. Eur. J. Hybrid Imaging 2023, 7, 24. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  58. Yang, B.; Dong, H.; Zhang, S.; Ming, S.; Yang, R.; Peng, Y.; Gao, X. PSMA PET vs. mpMRI for Lymph Node Metastasis of Prostate Cancer: A Systematic Review and Head-to-Head Comparative Meta-analysis. Acad. Radiol. 2025, 32, 2797–2814. [Google Scholar] [CrossRef] [PubMed]
  59. Yip, K.C.J.; Li, Y.-L.; Chen, S.; Ho, C.L.; Wartolowska, K. 68Ga-PSMA PET/CT and mpMRI for primary lymph node staging of intermediate to high-risk prostate cancer: A systematic review and meta-analysis of diagnostic test accuracy. Clin. Transl. Imaging 2021, 9, 523–537. [Google Scholar] [CrossRef]
  60. van Bergen, T.D.; Braat, A.J.A.T.; van den Berg, C.A.T.; Soeterik, T.F.W. Integration of prostate-specific membrane antigen-PET and multiparametric MRI for gross tumour volume definition in localised and locally advanced prostate cancer treated with image-guided radiotherapy. Curr. Opin. Urol. 2025, 35, 554–561. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  61. Midiri, F.; Vernuccio, F.; Purpura, P.; Alongi, P.; Bartolotta, T.V. Multiparametric MRI and Radiomics in Prostate Cancer: A Review of the Current Literature. Diagnostics 2021, 11, 1829. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  62. Alongi, P.; Messina, M.; Pepe, A.; Arnone, A.; Vultaggio, V.; Longo, C.; Fiasconaro, E.; Mirabile, A.; Ricapito, R.; Blasi, L.; et al. Prostate-specific membrane antigen-PET/CT may result in stage migration in prostate cancer: Performances, quantitative analysis, and potential criticism in the clinical practice. Nucl. Med. Commun. 2024, 45, 622–628. [Google Scholar] [CrossRef]
  63. Shen, Z.; Li, Z.; Li, Y.; Tang, X.; Lu, J.; Chen, L.; Cheng, Z.Z.; Liao, H.; Zhou, S. PSMA PET/CT for prostate cancer diagnosis: Current applications and future directions. J. Cancer Res. Clin. Oncol. 2025, 151, 155. [Google Scholar] [CrossRef]
  64. Grefve, J.; Strandberg, S.N.; Jonsson, J.; Lindberg, A.K.; Nilsson, E.; Bergh, A.; Söderkvist, K.; Karlsson, C.T.; Nedar, L.; Løgager, V.B.; et al. Local staging of de novo prostate cancer using mpMRI, PSMA-PET and PSMA-PET/mpMRI—A comparative study. EJNMMI Res. 2025, 15, 135. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  65. Emmett, L.; Buteau, J.; Papa, N.; Moon, D.; Thompson, J.; Roberts, M.J.; Rasiah, K.; Pattison, D.A.; Yaxley, J.; Thomas, P.; et al. The Additive Diagnostic Value of Prostate-specific Membrane Antigen Positron Emission Tomography Computed Tomography to Multiparametric Magnetic Resonance Imaging Triage in the Diagnosis of Prostate Cancer (PRIMARY): A Prospective Multicentre Study. Eur. Urol. 2021, 80, 682–689. [Google Scholar] [CrossRef] [PubMed]
  66. Woo, S.; Becker, A.S.; Leithner, D.; Mayerhoefer, M.E.; Friedman, K.P.; Tong, A.; Wise, D.R.; Taneja, S.S.; Zelefsky, M.J.; Vargas, H.A. Discordance between prostate MRI and PSMA-PET/CT: The next big challenge for primary prostate tumor assessment? Eur. Radiol. 2025, 35, 4043–4054. [Google Scholar] [CrossRef] [PubMed]
  67. Hope, T.A.; Eiber, M.; Armstrong, W.R.; Juarez, R.; Murthy, V.; Lawhn-Heath, C.; Behr, S.C.; Zhang, L.; Barbato, F.; Ceci, F.; et al. Diagnostic Accuracy of 68Ga-PSMA-11 PET for Pelvic Nodal Metastasis Detection Prior to Radical Prostatectomy and Pelvic Lymph Node Dissection: A Multicenter Prospective Phase 3 Imaging Trial. JAMA Oncol. 2021, 7, 1635–1642. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  68. Calais, J.; Czernin, J. PSMA Expression Assessed by PET Imaging Is a Required Biomarker for Selecting Patients for Any PSMA-Targeted Therapy. J. Nucl. Med. 2021, 62, 1489–1491. [Google Scholar] [CrossRef]
  69. Rauscher, I.; Karimzadeh, A.; Schiller, K.; Horn, T.; D’Alessandria, C.; Franz, C.; Wörther, H.; Nguyen, N.; Combs, S.E.; Weber, W.A.; et al. Detection efficacy of 18F-rhPSMA-7.3 PET/CT and impact on management in patients with biochemical recurrence of prostate cancer after radical prostatectomy and before potential salvage treatment. Nucl. Med. 2021, 62, 1719–1726. [Google Scholar] [CrossRef]
  70. Bagheri, H.; Mahdavi, S.R.; Geramifar, P.; Neshasteh-Riz, A.; Sajadi Rad, M.; Dadgar, H.; Arabi, H.; Zaidi, H. An update on the role of mpMRI and 68Ga-PSMA PET imaging in primary and recurrent prostate cancer. Clin. Genitourin. Cancer 2024, 22, 102076. [Google Scholar] [CrossRef]
  71. Liu, J.; Dunne, J.; Touijer, K.A.; Perera, M.; Lawrentschuk, N. The Performance and Role of PSMA PET Scans in Localised Prostate Cancer. Soc. Int. Urol. J. 2025, 6, 10. [Google Scholar] [CrossRef]
  72. Roberts, M.J.; Roberts, N.A.; Pelecanos, A.; Yaxley, J.W.; Harley, S.J.D.; Siriwardana, A.R.; Cullen, K.; Prior, M.; Lindsay, K.; Vela, I.; et al. A prospective, multi-centre trial of PSMA-PET compared to FDG-PET for staging of newly diagnosed high risk prostate cancer. EJNMMI Res. 2025, 15, 92. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  73. de Feria Cardet, R.E.; Hofman, M.S.; Segard, T.; Yim, J.; Williams, S.; Francis, R.J.; Frydenberg, M.; Lawrentschuk, N.; Murphy, D.G.; De Abreu Lourenco, R. Is Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography Imaging Cost-effective in Prostate Cancer: An Analysis Informed by the proPSMA Trial. Eur. Urol. 2021, 79, 413–418. [Google Scholar] [CrossRef] [PubMed]
  74. Holzgreve, A.; Unterrainer, M.; Calais, J.; Adams, T.; Oprea-Lager, D.E.; Goffin, K.; Lopci, E.; Unterrainer, L.M.; Kramer, K.K.M.; Schmidt-Hegemann, N.S.; et al. Is PSMA PET/CT cost-effective for the primary staging in prostate cancer? First results for European countries and the USA based on the proPSMA trial. Eur. J. Nucl. Med. Mol. Imaging 2023, 50, 3750–3754. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  75. Turkbey, B.; Huisman, H.; Fedorov, A.; Macura, K.J.; Margolis, D.J.; Panebianco, V.; Oto, A.; Schoots, I.G.; Siddiqui, M.M.; Moore, C.M.; et al. Requirements for AI development and reporting for MRI prostate cancer detection in biopsy-naive men: PI-RADS Steering Committee, version 1.0. Radiology 2025, 315, e240140. [Google Scholar] [CrossRef]
  76. Mottet, N.; van den Bergh, R.C.N.; Briers, E.; Van den Broeck, T.; Cumberbatch, M.G.; De Santis, M.; Fanti, S.; Fossati, N.; Gandaglia, G.; Gillessen, S.; et al. EAU-EANM-ESTRO-ESUR-SIOG guidelines on prostate cancer—2020 update. Part 1: Screening, diagnosis, and local treatment with curative intent. Eur. Urol. 2021, 79, 243–262. [Google Scholar] [CrossRef] [PubMed]
  77. Caracciolo, M.; Castello, A.; Lopci, E. PSMA PET/CT Versus mpMRI for the Detection of Clinically Significant Prostate Cancer: An Updated Overview. Semin. Nucl. Med. 2024, 54, 30–38. [Google Scholar] [CrossRef] [PubMed]
  78. Privé, B.M.; Govers, T.M.; Israël, B.; Janssen, M.J.R.; Timmermans, B.J.R.; Peters, S.M.B.; de Groot, M.; Zámecnik, P.; Wijn, S.R.W.; Hoepping, A.; et al. A cost-effectiveness study of PSMA-PET/CT for the detection of clinically significant prostate cancer. Eur. J. Nucl. Med. Mol. Imaging 2025, 52, 3159–3169. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  79. Phillipi, M.; Choung, D.; Ho, E.; Anavim, S.; Saeed, S.; Shu, C.; Shi, J.; Glavis-Bloom, J.; Gupta, A.; Joshi, A.; et al. Diagnostic performance of PSMA PET/CT, multiparametric MRI, and combined imaging for local prostate cancer recurrence after radical prostatectomy. Abdom. Imaging 2025. [Google Scholar] [CrossRef] [PubMed]
  80. Zapatero, A.; Roch, M.; Castro Tejero, P.; Büchser, D.; Martin de Vidales, C.; González, S.; Rodríguez, P.; San Jose, L.A.; Celada, G.; Murillo, M.T. MRI-guided focal boost to dominant intraprostatic lesion using volumetric modulated arc therapy in prostate cancer. Results of a phase II trial. Br. J. Radiol. 2022, 95, 20210683. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  81. Webster, M.; Podgorsak, A.; Li, F.; Zhou, Y.; Jung, H.; Yoon, J.; Dona Lemus, O.; Zheng, D. New Approaches in Radiotherapy. Cancers 2025, 17, 1980. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  82. Evangelista, L.; Mansi, L.; Spadafora, M. PSMA-Targeted radiopharmaceuticals: From diagnosis to risk & quality of life. Eur. J. Nucl. Med. Mol. Imaging 2025, 53, 19–23. [Google Scholar] [CrossRef]
  83. Kunte, S.C.; Holzgreve, A.; Unterrainer, M.; Zahner, J.; Schmid, H.P.; Schöll, M.; Blajan, I.; Sheikh, G.T.; Mehrens, D.; Casuscelli, J.; et al. Changes of Prostate-Specific Membrane Antigen-Radioligand Uptake on PET with Systemic Therapy in Patients with Metastatic Renal Cell Carcinoma. Cancers 2025, 17, 1736. [Google Scholar] [CrossRef] [PubMed]
  84. Argow, M.J.; Hupfeld, S.; Schenke, S.A.; Neumann, S.; Damm, R.; Vogt, J.; Guer, M.; Wuestemann, J.; Schostak, M.; Fischbach, F.; et al. Comparison of mpMRI and 68Ga-PSMA-PET/CT in the Assessment of the Primary Tumors in Predominant Low-/Intermediate-Risk Prostate Cancer. Diagnostics 2025, 15, 1358. [Google Scholar] [CrossRef]
  85. Lopez-Valcarcel, M.; Lopez-Campos, F.; Zafra-Martín, J.; Cienfuegos Belmonte, I.; Subiela, J.D.; Ruiz-Vico, M.; Fernandez Alonso, S.; Garcia Cuesta, J.A.; Couñago, F. Biomarkers in Localized Prostate Cancer: From Diagnosis to Treatment. Int. J. Mol. Sci. 2025, 26, 7667. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  86. Urso, L.; Badrane, I.; Manco, L.; Castello, A.; Lancia, F.; Collavino, J.; Crestani, A.; Castellani, M.; Cittanti, C.; Bartolomei, M.; et al. The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness. J. Clin. Med. 2025, 14, 3318. [Google Scholar] [CrossRef]
  87. Mercier, J.; Bento, L.; Cassou-Mounat, T.; Prudhomme, T.; Lagarde, S.; Game, X.; Soulie, M.; Thoulouzan, M.; Bajeot, A.-S.; Roumiguie, M. Post-HIFU surveillance of localized prostate cancer: Role of PSMA-PET imaging versus the standard PSA–mpMRI protocol. World J. Urol. 2026, 44, 68. [Google Scholar] [CrossRef]
  88. Scott, R.; Misser, S.K.; Cioni, D.; Neri, E. PI-RADS v2.1: What has changed and how to report. S. Afr. J. Radiol. 2021, 25, 2062. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  89. Ma, L.; Hao, Y.; Zhai, L.; Zhang, W.; Cao, X.; Jia, K. Which PSMA PET/CT interpretation criteria most effectively diagnose prostate cancer? a retrospective cohort study. BMC Med. Imaging 2025, 25, 23. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  90. Karpinski, M.J.; Hoberück, S.; Fendler, W.P.; Civan, C.; Bundschuh, R.A.; Thomas, C.; Bjartell, A.; Trägårdh, E.; Soeterik, T.F.W.; Evangelista, L.; et al. Association Between the PRIMARY Score at Staging Prostate-specific Membrane Antigen Positron Emission Tomography and Overall Survival Among Patients with Newly Diagnosed Prostate Cancer: Findings from the International, Multicenter PROMISE Registry. Eur. Urol. 2025, 89, 123–127. [Google Scholar] [CrossRef] [PubMed]
  91. Werner, R.A.; Hartrampf, P.E.; Fendler, W.P.; Serfling, S.E.; Derlin, T.; Higuchi, T.; Pienta, K.J.; Gafita, A.; Hope, T.A.; Pomper, M.G.; et al. Prostate-specific Membrane Antigen Reporting and Data System Version 2.0. Eur. Urol. 2023, 84, 491–502. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  92. Guo, E.; Xu, L.; Zhang, D.; Zhang, J.; Zhang, X.; Bai, X.; Chen, L.; Peng, Q.; Zhang, G.; Jin, Z.; et al. Diagnostic performance of MRI in detecting prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL: A systematic review and meta-analysis. Insights Imaging 2024, 15, 147. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  93. Giambelluca, D.; Cannella, R.; Vernuccio, F.; Comelli, A.; Pavone, A.; Salvaggio, L.; Galia, M.; Midiri, M.; Lagalla, R.; Salvaggio, G. PI-RADS 3 Lesions: Role of Prostate MRI Texture Analysis in the Identification of Prostate Cancer. Curr. Probl. Diagn. Radiol. 2021, 50, 175–185. [Google Scholar] [CrossRef]
  94. Chaddad, A.; Tan, G.; Liang, X.; Hassan, L.; Rathore, S.; Desrosiers, C.; Katib, Y.; Niazi, T. Advancements in MRI-Based Radiomics and Artificial Intelligence for Prostate Cancer: A Comprehensive Review and Future Prospects. Cancers 2023, 15, 3839. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  95. Cavallo, A.U.; Stanzione, A.; Ponsiglione, A.; Trotta, R.; Fanni, S.C.; Ghezzo, S.; Vernuccio, F.; Klontzas, M.E.; Triantafyllou, M.; Ugga, L.; et al. Prostate cancer MRI methodological radiomics score: A EuSoMII radiomics auditing group initiative. Eur. Radiol. 2025, 35, 1157–1165. [Google Scholar] [CrossRef] [PubMed]
  96. Ma, J.; Wang, C.; Wang, M.; Ren, C.; Huang, Z.; Chen, Y.; Xiong, S.; Yang, J.; Liu, M.; Huo, L. The integrated diagnostic strategy of performing PSMA PET/CT followed by MRI improves the diagnostic accuracy of prostate cancer. Eur. J. Nucl. Med. Mol. Imaging, 2026; ahead of print. [Google Scholar] [CrossRef] [PubMed]
  97. Kolade, O.U.; Brink, A.; Ayeni, A.O.; More, S.; Holness, J. Optimizing PSMA scintigraphy for resource limited settings—A retrospective comparative study. Cancer Imaging 2024, 24, 46. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  98. Cornford, P.; van den Bergh, R.C.N.; Briers, E.; Van den Broeck, T.; Brunckhorst, O.; Darraugh, J.; Eberli, D.; De Meerleer, G.; De Santis, M.; Farolfi, A.; et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer—2024 Update. Part I: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur. Urol. 2024, 86, 148–163. [Google Scholar] [CrossRef] [PubMed]
  99. Saxena, S.; Jena, B.; Gupta, N.; Das, S.; Sarmah, D.; Bhattacharya, P.; Nath, T.; Paul, S.; Fouda, M.M.; Kalra, M.; et al. Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine. Cancers 2022, 14, 2860. [Google Scholar] [CrossRef]
  100. Scavuzzo, A.; Pasini, G.; Perez, O.G.; Jimenez Rios, M.A.; Hernández, M.A.; Pedrero-Piedras, R.; Pérez Montiel, M.D.; Moreno, N.S.; Russo, G.; Stefano, A. Radiomics-based machine learning models for predicting genomic alterations in metastatic prostate cancer using PSMA PET imaging: A pilot study. EJNMMI Rep. 2025, 9, 42. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  101. Filippi, L.; Urso, L.; Manco, L.; Olivieri, M.; Badrane, I.; Evangelista, L. Insights into pet-based radiogenomics in oncology: An updated systematic review. Eur. J. Nucl. Med. Mol. Imaging 2025, 52, 4184–4199. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  102. Leung, K.H.; Rowe, S.P.; Leal, J.P.; Ashrafinia, S.; Sadaghiani, M.S.; Chung, H.W.; Dalaie, P.; Tulbah, R.; Yin, Y.; VanDenBerg, R.; et al. Deep learning and radiomics framework for PSMA-RADS classification of prostate cancer on PSMA PET. EJNMMI Res. 2022, 12, 76. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  103. Dadgar, H.; Hong, X.; Karimzadeh, R.; Ibragimov, B.; Majidpour, J.; Arabi, H.; Al-Ibraheem, A.; Khalaf, A.N.; Anwar, F.M.; Marafi, F.; et al. The value of artificial intelligence in PSMA PET: A pathway to improved efficiency and results. Q. J. Nucl. Med. Mol. Imaging 2025, 69, 157–173. [Google Scholar] [CrossRef] [PubMed]
Medicina 62 00610 g001
Figure 1. MRI and PSMA-PET/CT in prostate cancer staging. Long Axial Field-of-View (LAFOV) Total-Body PET/CT (194 cm uEXPLORER, United Imaging, Shanghai, China) with 18F-Piflufolastat (2.64 MBq/kg) in a patient with Gleason 8 (4 + 4) and PSA 14.2 ng/mL. Panels: (A) T2-weighted MRI; (B) ADC; (C) high b-value DWI; (D) contrast-enhanced T1; (E) attenuation-corrected PSMA-PET; (F) low-dose CT; (G) fused PET/CT; (H) PET/MRI-DWI fusion; (I) PET MIP. PET tracer distribution is visualized using the ‘Warm-Metal’ linear color scale. Image reconstruction and post-processing were performed using United Imaging Healthcare PET/CT and CT Image Post-processing Software (uWS-MI:R002.32.0.1749877; uWS-CT:F006.34.0.1749877). Higher metabolic activity or tracer avidity is represented by the transition from cooler tones (black/green) to warmer tones (orange/white). MRI shows a left-lobe lesion with mild diffusion restriction; PET identifies two tracer-avid areas, including a posterior focus near the capsule and rectal wall not clearly seen on MRI. MRI and PET complement each other for accurate local staging. Images courtesy of San Pietro Fatebenefratelli Hospital, Rome.
Figure 1. MRI and PSMA-PET/CT in prostate cancer staging. Long Axial Field-of-View (LAFOV) Total-Body PET/CT (194 cm uEXPLORER, United Imaging, Shanghai, China) with 18F-Piflufolastat (2.64 MBq/kg) in a patient with Gleason 8 (4 + 4) and PSA 14.2 ng/mL. Panels: (A) T2-weighted MRI; (B) ADC; (C) high b-value DWI; (D) contrast-enhanced T1; (E) attenuation-corrected PSMA-PET; (F) low-dose CT; (G) fused PET/CT; (H) PET/MRI-DWI fusion; (I) PET MIP. PET tracer distribution is visualized using the ‘Warm-Metal’ linear color scale. Image reconstruction and post-processing were performed using United Imaging Healthcare PET/CT and CT Image Post-processing Software (uWS-MI:R002.32.0.1749877; uWS-CT:F006.34.0.1749877). Higher metabolic activity or tracer avidity is represented by the transition from cooler tones (black/green) to warmer tones (orange/white). MRI shows a left-lobe lesion with mild diffusion restriction; PET identifies two tracer-avid areas, including a posterior focus near the capsule and rectal wall not clearly seen on MRI. MRI and PET complement each other for accurate local staging. Images courtesy of San Pietro Fatebenefratelli Hospital, Rome.
Medicina 62 00610 g001
Medicina 62 00610 g002
Figure 2. Decision-Flow Framework for Integrated Imaging. This schematic comparison clarifies that the proposed paradigm does not replace established diagnostic standards but seeks to harmonize anatomical and molecular data earlier in the decision process.
Figure 2. Decision-Flow Framework for Integrated Imaging. This schematic comparison clarifies that the proposed paradigm does not replace established diagnostic standards but seeks to harmonize anatomical and molecular data earlier in the decision process.
Medicina 62 00610 g002
Medicina 62 00610 g003
Figure 3. MRI and PSMA-PET/CT in intra-prostatic relapse evaluation. Long Axial Field-of-View (LAFOV) Total-Body PET/CT (194 cm uEXPLORER, United Imaging) with 18F-Piflufolastat (3.35 MBq/kg) in a patient with PSA 3.98 ng/mL, Gleason 6 (3 + 3), post-radiotherapy. Panels: (A) ADC; (B) high b-value DWI; (C) T2-weighted MRI; (D) attenuation-corrected PSMA-PET; (E) low-dose CT; (F) fused PET/CT; (G) axial PET/T2 fusion; (H) sagittal T2; (I) sagittal PET/T2 fusion; (J) PET MIP. PET tracer distribution is visualized using the ‘Warm-Metal’ linear color scale. Image reconstruction and post-processing were performed usingUnited Imaging Healthcare PET/CT and CT Image Post-processing Software (uWS-MI:R002.32.0.1749877; uWS-CT:F006.34.0.1749877), where higher metabolic activity or tracer avidity is represented by the transition from cooler tones (black/green) to warmer tones (orange/white). MRI shows a focal lesion with diffusion restriction and T2 hypointensity, matching PET uptake along the anterior midline. MRI clarifies urethral position, confirming true intraprostatic relapse. Complementary MRI-PET improves lesion characterization. Images courtesy of Nuclear Medicine Centre, San Pietro Fatebenefratelli Hospital, Rome, Italy.
Figure 3. MRI and PSMA-PET/CT in intra-prostatic relapse evaluation. Long Axial Field-of-View (LAFOV) Total-Body PET/CT (194 cm uEXPLORER, United Imaging) with 18F-Piflufolastat (3.35 MBq/kg) in a patient with PSA 3.98 ng/mL, Gleason 6 (3 + 3), post-radiotherapy. Panels: (A) ADC; (B) high b-value DWI; (C) T2-weighted MRI; (D) attenuation-corrected PSMA-PET; (E) low-dose CT; (F) fused PET/CT; (G) axial PET/T2 fusion; (H) sagittal T2; (I) sagittal PET/T2 fusion; (J) PET MIP. PET tracer distribution is visualized using the ‘Warm-Metal’ linear color scale. Image reconstruction and post-processing were performed usingUnited Imaging Healthcare PET/CT and CT Image Post-processing Software (uWS-MI:R002.32.0.1749877; uWS-CT:F006.34.0.1749877), where higher metabolic activity or tracer avidity is represented by the transition from cooler tones (black/green) to warmer tones (orange/white). MRI shows a focal lesion with diffusion restriction and T2 hypointensity, matching PET uptake along the anterior midline. MRI clarifies urethral position, confirming true intraprostatic relapse. Complementary MRI-PET improves lesion characterization. Images courtesy of Nuclear Medicine Centre, San Pietro Fatebenefratelli Hospital, Rome, Italy.
Medicina 62 00610 g003
Table 1. Quantitative Imaging Biomarkers and Clinical Correlates. Overview of established and emerging quantitative imaging biomarkers from mpMRI and PSMA PET and their reported correlations with tumor aggressiveness, burden, and risk stratification.
Table 1. Quantitative Imaging Biomarkers and Clinical Correlates. Overview of established and emerging quantitative imaging biomarkers from mpMRI and PSMA PET and their reported correlations with tumor aggressiveness, burden, and risk stratification.
ModalityBiomarkerClinical Correlation
mpMRIADCminGleason grade, aggressiveness
PSMA PETSUVmaxTumor burden, progression
HybridADC + SUVImproved risk prediction
Table 2. Comparative Strengths and Limitations of mpMRI vs. PSMA PET. Comparison of the principal diagnostic capabilities, quantitative biomarkers, and limitations of mpMRI and PSMA PET, highlighting their complementary roles in local tumor characterization and whole-body staging.
Table 2. Comparative Strengths and Limitations of mpMRI vs. PSMA PET. Comparison of the principal diagnostic capabilities, quantitative biomarkers, and limitations of mpMRI and PSMA PET, highlighting their complementary roles in local tumor characterization and whole-body staging.
FeaturempMRIPSMA PET
Primary tumor detectionExcellent (T2/DWI/ADC)Moderate
Local staging (ECE, SVI)ExcellentLimited
Nodal metastasesLimited (size-based)Excellent
Distant metastasesPoorExcellent
Quantitative biomarkersADCSUV, TBR
LimitationsTZ lesions, inter-reader variabilityFalse positives, PSMA-negative tumors
Table 3. Clinical Impact of Integrated mpMRI + PSMA PET by Disease State. Summary of key clinical scenarios in which combined mpMRI and PSMA PET imaging improves risk stratification, disease localization, and treatment decision-making, supported by representative studies.
Table 3. Clinical Impact of Integrated mpMRI + PSMA PET by Disease State. Summary of key clinical scenarios in which combined mpMRI and PSMA PET imaging improves risk stratification, disease localization, and treatment decision-making, supported by representative studies.
Clinical ScenarioAdded Value of IntegrationRepresentative Evidence
Biopsy-naïve patientsImproved risk stratification[7]
Intermediate-risk PCaOccult nodal detection[67]
Biochemical recurrenceLocalization at PSA < 0.5[69]
Radiotherapy planningField modification[70]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Pugliesi, R.A.; Cannella, R.; Ben Mansour, K.; Di Biagio, D.; Alongi, P. Integrating Multiparametric MRI and PSMA PET Imaging in Prostate Cancer: Toward a Unified Diagnostic and Risk-Stratification Paradigm. Medicina 2026, 62, 610. https://doi.org/10.3390/medicina62030610

AMA Style

Pugliesi RA, Cannella R, Ben Mansour K, Di Biagio D, Alongi P. Integrating Multiparametric MRI and PSMA PET Imaging in Prostate Cancer: Toward a Unified Diagnostic and Risk-Stratification Paradigm. Medicina. 2026; 62(3):610. https://doi.org/10.3390/medicina62030610

Chicago/Turabian Style

Pugliesi, Rosa Alba, Roberto Cannella, Karim Ben Mansour, Daniele Di Biagio, and Pierpaolo Alongi. 2026. "Integrating Multiparametric MRI and PSMA PET Imaging in Prostate Cancer: Toward a Unified Diagnostic and Risk-Stratification Paradigm" Medicina 62, no. 3: 610. https://doi.org/10.3390/medicina62030610

APA Style

Pugliesi, R. A., Cannella, R., Ben Mansour, K., Di Biagio, D., & Alongi, P. (2026). Integrating Multiparametric MRI and PSMA PET Imaging in Prostate Cancer: Toward a Unified Diagnostic and Risk-Stratification Paradigm. Medicina, 62(3), 610. https://doi.org/10.3390/medicina62030610

Article Metrics

Back to TopTop