Search Results (189)

Background/Objectives: Multiparametric MRI (mpMRI) is widely established as the standard imaging modality for detecting clinically significant prostate cancer (csPCa), yet it can be limited by cost, accessibility, and the need for specialized radiologist interpretation. Micro-ultrasound (micro-US) has recently emerged as a more accessible alternative imaging modality. This review evaluates whether the evidence base for micro-US meets thresholds comparable to those that led to MRI’s guideline adoption, synthesizes diagnostic performance data compared to mpMRI, and outlines future research priorities to define its clinical role. Methods: A targeted literature review of PubMed, Embase, and the Cochrane Library was conducted for studies published between 2014 and May 2025 evaluating micro-US in csPCa detection. Search terms included “micro-ultrasound,” “ExactVu,” “PRI-MUS,” and related terminology. Study relevance was assessed independently by the authors. Extracted data included csPCa detection rates, modality concordance, and diagnostic accuracy, and were synthesized and, rarely, restructured to facilitate study comparisons. Results: Micro-US consistently demonstrated non-inferiority to mpMRI for csPCa detection across retrospective studies, prospective cohorts, and meta-analyses. Several studies reported discordant csPCa lesions detected by only one modality, highlighting potential complementarity. The recently published OPTIMUM randomized controlled trial offers the strongest individual-trial evidence to date in support of micro-US non-inferiority. Conclusions: Micro-US shows potential as an alternative or adjunct to mpMRI for csPCa detection. However, additional robust multicenter studies are needed to achieve the evidentiary strength that led mpMRI to distinguish itself in clinical guidelines. Full article

Introduction: The multigene molecular testing of prostate cancer tissue after biopsy provides individualized information to guide further management. The utility of selective genetic testing for MRI-visible target versus systematic cancer in patients as well as during different time points of active surveillance (AS) is unknown. The objective of this study was to compare Prolaris^TM results of MRI-target cancers versus systematic cancers on prostate needle biopsy as well as both during consideration for initial AS candidacy and candidacy for remaining on AS. Methods: Our prospectively maintained institutional multiparametric (mp) MRI prostate cancer active surveillance database (2013–2024) was queried for patients that underwent Prolaris^TM genetic testing of positive biopsy cores. Baseline information for PSA, PSA density, and Prolaris^TM calculated data were collected. Information on the timing of the Prolaris testing, defined as during the initial cancer diagnostic biopsy or on a subsequent confirmatory biopsy was collected. SPSS v29.0 was used to compare the selective Prolaris^TM results of MRI-target cancers versus systematic cancers during different points of AS. Results: 264 patients with a Prolaris^TM test were identified, 86 with MRI-target and 178 on systematic cancers. 182 Prolaris^TM tests were sent on a diagnostic biopsy and 81 on a subsequent biopsy. Overall, MRI-target cancers had similar risk scores (3.23 vs. 3.14, p = 0.18). Prolaris^TM scores were higher for GG2 systematic than GG1 target cancers (3.40 vs. 3.18, p = 0.023). The GG2 systematic lesion cohort also had higher predicted the 10-year disease-specific mortality (DSM) (3.40% vs. 2.30%, p < 0.01) and 10-year metastasis risk (1.90% vs. 1.20%, p = 0.013), and more aggressive recommended treatment. Analyses of the Prolaris^TM results sent during a diagnostic biopsy yielded similar results. Finally, on an analysis of the Prolaris^TM results sent during subsequent biopsy, a systematic GG2 biopsy was noted to have a higher 10-year DSM and metastasis rate, but similar risk scores and treatment recommendations. Conclusions: Prolaris^TM tests can be sent at multiple time points of AS, and selectively for MRI-visible versus higher grade cancers. There is no consistent association between MRI-visible cancer and Prolaris risk profile. When utilizing multigene molecular testing in prostate cancer, each individual patient must be evaluated to decide the appropriate level of care. Full article

Prostate cancer is the most commonly diagnosed malignancy in men and continues to be a leading cause of cancer-related mortality. Accurate and timely diagnosis is essential for distinguishing clinically significant tumors from indolent lesions and for informing treatment decisions. Multiparametric magnetic resonance imaging (mpMRI) has revolutionized prostate cancer detection by enabling precise lesion localization, risk stratification, and improved biopsy targeting. Fusion biopsy, which combines mpMRI findings with real-time transrectal ultrasonography (TRUS), has emerged as a highly effective method for sampling suspicious lesions. This review provides an integrated anatomical, epidemiological, technical, and clinical overview that highlights the evolving role of fusion biopsy in contemporary prostate cancer diagnostics. We also explore emerging strategies such as penumbra-targeted sampling, discuss ongoing clinical challenges, and examine the impact of biopsy underestimation and lack of standardization. Compared to conventional systematic biopsy, mpMRI-TRUS fusion biopsy improves the detection of clinically significant prostate cancer while reducing the overdiagnosis of low-risk tumors. To our knowledge, few recent reviews have comprehensively synthesized current clinical guidelines, emerging biopsy techniques, and future directions within a single narrative. mpMRI-TRUS-guided fusion biopsy represents a major advancement in the prostate cancer diagnostic pathway, promoting precision oncology by reducing overtreatment and facilitating individualized patient care. This review aims to assist clinicians in adopting biopsy innovations that enhance diagnostic accuracy and improve patient outcomes. Full article

Background/Objectives: Prostate cancer is the second most common malignancy in men, and robot-assisted radical prostatectomy (RARP) has become a preferred treatment for localized disease. Postoperative urinary continence is a key determinant of quality of life. The aim of this study was to evaluate the preoperative patient characteristics and multiparametric magnetic resonance imaging (mpMRI) data that determine early postoperative continence in patients who underwent robotic radical prostatectomy at our clinic. Methods: In this study, patients who underwent robotic radical prostatectomy at our clinic between March 2020 and June 2022 were evaluated. The patients’ demographic data, preoperative PSA levels, digital rectal examination findings, preoperative lower urinary tract symptoms, sexual function, mpMRI findings, Briganti scores, surgical techniques used during the procedure and postoperative continence status were assessed. Results: A total of 111 patients were included in the study. The mean age of the patients was 61.1 years. The median follow-up duration was twelve months. According to the postoperative continence status, 22% of the patients were incontinent, 53% had moderate continence and 24% were fully continent in the first month. At the third month, 16.8% of the patients were incontinent, 31.3% had moderate continence and 51.8% were fully continent. At the one-year postoperative follow-up, the percentages of incontinent, moderately continent and fully continent patients were 4.8%, 13.2% and 81.9%, respectively. Urethral width in mpMRI (p: 0.012), pelvic transverse (p: 0.002) and AP (anterior–posterior) diameters (p: 0.033), preoperative IPSS scores (p: 0.033) and the presence of bilateral nerve-sparing surgery (p: 0.047) were found to be associated with postoperative urinary continence. No significant differences were found between groups regarding the relationship of other parameters evaluated by mpMRI with continence. Conclusions: In our study, preoperative IPSS scores, urethral width in mpMRI, pelvic transverse and AP diameters and the performance of nerve-sparing surgery were associated with early postoperative continence. Further studies with larger patient populations are needed to better understand the long-term predictors of postoperative urinary incontinence following radical prostatectomy. Full article

Background: Prostate cancer (PCa) represents a matter at the forefront of healthcare, being divided into clinically significant (csPCa) and indolent PCa based on prognostic and treatment options. Although multi-parametric magnetic resonance imaging (mpMRI) has enabled significant advances, it cannot differentiate between the aforementioned categories; therefore, in order to render the initial diagnosis, invasive procedures such as transrectal prostate biopsy are still necessary. In response to these challenges, artificial intelligence (AI)-based algorithms combined with radiomics features offer the possibility of creating a textural pixel pattern-based surrogate, which has the potential of correlating the medical imagery with the pathological report in a one-to-one manner. Objective: The aim of the present study was to develop a machine learning model that can differentiate indolent from csPCa lesions, as well as individually classifying each nodule into corresponding ISUP grades prior to prostate biopsy, using textural features derived from mpMRI T2WI acquisitions. Materials and Methods: The study was conducted in 154 patients and 201 individual prostatic lesions. All cases were scanned using the same 1.5 Tesla mpMRI machine, employing a standard protocol. Each nodule was manually delineated using the 3D Slicer platform (version 5.2.2) and textural parameters were derived using the PyRadiomics database (version 3.1.0). We compared three machine learning classification models (Random Forest, Support Vector Machine, and Logistic Regression) in full, partial and no correlation settings, in order to differentiate between indolent and csPCa, as well as between ISUP 2 and ISUP 3 lesions. Results: The median age was 65 years (IQR: 61–69), the mean PSA value was 10.27 ng/mL, and 76.61% of the segmented lesions had a PI-RADS score of 4 or higher. Overall, the highest performance was registered for the Random Forest model in the partial correlation setting, differentiating between indolent and csPCa and between ISUP 2 versus ISUP 3 lesions, with accuracies of 88.13% and 82.5%, respectively. When the models were trained on combined clinical data and radiomic signatures, these accuracies increased to 91.11% and 91.39%, respectively. Conclusions: We developed a machine learning decision support tool that accurately predicts the ISUP grade prior to prostate biopsy, based on the textural features extracted from T2 MRI acquisitions. Full article

Background/Objectives: The diagnostic approach to prostate cancer (PCa) has evolved from systematic biopsies to imaging-guided strategies that improve detection of clinically significant PCa (csPCa) while reducing overdiagnosis. Multiparametric magnetic resonance imaging (mpMRI) has emerged as the gold standard for pre-biopsy evaluation, while micro-ultrasound (MicroUS) offers a promising alternative with real-time imaging capabilities. Methods: We examined the principles, image interpretation frameworks (Prostate Imaging Reporting and Data System (PI-RADS) and Prostate Risk Identification using Micro UltraSound (PRI-MUS)), and clinical applications of mpMRI and MicroUS, comparing their diagnostic accuracy in biopsy-naïve patients, repeat biopsy scenarios, active surveillance, and staging. Results: mpMRI improves csPCa detection, reduces unnecessary biopsies, and enhances risk stratification. Landmark studies such as PRECISION (Prostate Evaluation for Clinically Important Disease: Sampling Using Image Guidance or Not?) and PRIME (Prostate Imaging Using MRI±Contrast Enhancement) confirm its superiority over systematic biopsy. However, mpMRI remains resource-intensive, with limitations in accessibility and interpretation variability. Conversely, MicroUS, with its high-resolution real-time imaging, shows non-inferiority to mpMRI and potential advantages in magnetic resonance imaging (MRI)-ineligible patients. It improves lesion visualization and biopsy targeting, with ongoing trials such as OPTIMUM (Optimization of prostate biopsy—Micro-Ultrasound versus MRI) evaluating its standalone efficacy. Conclusions: mpMRI and MicroUS are complementary modalities in PCa diagnosis. While mpMRI remains the preferred imaging standard, MicroUS offers an alternative, particularly in patients with MRI contraindications. Combining these techniques could enhance diagnostic accuracy, reduce unnecessary interventions, and refine active surveillance strategies. Future research should focus on integrating both modalities into standardized diagnostic pathways for a more individualized approach. Full article

While multi-parametric magnetic resonance imaging (mpMRI) is known to be a specific and reliable modality for the diagnosis of non-metastatic prostate cancer (PC), positron emission tomography (PET) using ⁶⁸Ga labeled ligands targeting the prostate-specific membrane antigen (PSMA) is known for its reliable detection of prostate cancer, being the most sensitive modality for the assessment of the extra-prostatic extension of the disease and the establishment of a diagnosis, even before biopsy. Background/Objectives: Here, we compared these modalities in regards to the localization of intraprostatic cancer lesions prior to local HDR brachytherapy. Methods: A cohort of 27 patients received both mpMRI and PSMA-PET/CT. Based on 24 intraprostatic segments, two readers each scored the risk of tumor-like alteration in each imaging modality. The detectability was evaluated using receiver operating characteristic (ROC) analysis. The histopathological findings from biopsy were used as the gold standard in each segment. In addition, we applied a patient-based “congruence” concept to quantify the interobserver and intermodality agreement. Results: For the ROC analysis, we included 447 segments (19 patients), with their respective histological references. The two readers of the MRI reached an AUC of 0.770 and 0.781, respectively, with no significant difference (p = 0.75). The PET/CT readers reached an AUC of 0.684 and 0.608, respectively, with a significant difference (p < 0.001). The segment-wise intermodality comparison showed a significant superiority of MRI (AUC = 0.815) compared to PET/CT (AUC = 0.690) (p = 0.006). Via a patient-based analysis, a superiority of MRI in terms of relative agreement with the biopsy result was observed (n = 19 patients). We found congruence scores of 83% (MRI) and 76% (PET/CT, p = 0.034), respectively. Using an adjusted “near total agreement” score (adjacent segments with positive scores of 4 or 5 counted as congruent), we found an increase in the agreement, with a score of 96.5% for MRI and 92.7% for PET/CT, with significant difference (p = 0.024). Conclusions: This study suggests that in a small collective of low-/intermediate risk prostate cancer, mpMRI is superior for the detection of intraprostatic lesions as compared to PSMA-PET/CT. We also found a higher relative agreement between MRI and biopsy as compared to that for PET/CT. However, further studies including a larger number of patients and readers are necessary to draw solid conclusions. Full article

Prostate cancer (PCa) is one of the most common malignancies among men worldwide. While prostate-specific antigen (PSA) screening has improved early detection, it has also led to significant challenges regarding overdiagnosis and overtreatment. Overdiagnosis involves identifying indolent tumors unlikely to affect a patient’s lifespan, while overtreatment refers to unnecessary interventions that can cause adverse effects such as urinary incontinence, erectile dysfunction, and a reduced quality of life. This review highlights contributing factors, including the limitations of PSA testing, advanced imaging techniques like multi-parametric MRI (mpMRI), medical culture, and patient expectations. The analysis emphasizes the need for refining screening protocols, integrating novel biomarkers (e.g., PCA3, TMPRSS2-ERG), and adopting conservative management strategies such as active surveillance to minimize harm. Risk-based screening and shared decision-making are critical to balancing the benefits of early detection with the risks of unnecessary treatment. Additionally, systemic healthcare factors like financial incentives and malpractice concerns exacerbate overuse. This review advocates for updated clinical guidelines and personalized approaches to optimizing patient outcomes while reducing the strain on healthcare resources. Addressing overdiagnosis and overtreatment through targeted interventions will improve the quality of life for PCa patients and enhance the efficiency of healthcare systems. Full article

A male in his 60s presented with a four-month history of dysuria and lower urinary tract symptoms (LUTS). He had a history of elevated PSA and benign prostatic hyperplasia (BPH), previously treated with transurethral resection of the prostate (TURP). Multiparametric MRI (MP-MRI) revealed a PI-RADS 5 lesion, raising suspicion of malignancy. However, histopathological analysis from MRI fusion-targeted biopsies confirmed tuberculous prostatitis. The patient was treated with antituberculosis drugs, resulting in symptomatic improvement and a significant PSA decline. This case highlights the diagnostic challenge of distinguishing tuberculous prostatitis from prostate cancer, particularly in tuberculosis-endemic regions. Our literature review reveals that patients with tuberculous prostatitis undergoing MRI are at least 50 years old, originate from endemic areas, and exhibit PI-RADS scores ranging from 2 to 5, indicating inter-rater variability. Histopathological confirmation remains essential in cases with ambiguous imaging and clinical findings. Full article

Background: Prostate cancer is a major cause of cancer-related mortality among men, with approximately 15% of newly diagnosed patients having pelvic lymph node metastasis (PLNM). For this reason, PLNM identification before localized PCa treatment would significantly impact treatment planning, clinical judgment, and patient outcome prediction. Radiomics has gained popularity for its ability to predict tumor behavior and prognosis without invasive procedures. Magnetic resonance imaging (MRI) is widely used in radiomic workups, particularly for prostate cancer. This study aims to predict lymph node invasion in prostate cancer patients using clinical information and mp-MRI radiomics features extracted from the suspicious nodule, prostate gland, and periprostatic adipose tissue (PPAT). Methods: A retrospective review of 85 patients who underwent mp-MRI at our radiology department between 2016 and 2022 was conducted. This study included patients who underwent prostatectomy and lymphadenectomy with complete histological examination and previous staging mp-MRI and were divided into two groups based on lymph node status (positive/negative). Data were collected from each patient, including clinical information, radiomics, and semantic data (such as tumor MRI characteristics, histological tumor details, and lymph node status (LNS)). MRI exams were conducted using a 1.5-T system and were used to study the prostate gland. A three-year resident manually segmented the prostate nodule, prostatic gland, and periprostatic tissue using an open-source segmentation program. A random forest (RF) machine learning model was developed and tested using Chat-GPT version 4.0 software. The model’s performance in predicting LNS was assessed using accuracy, precision, recall, F1 score, and area under the curve (AUC) receiver operating characteristic (ROC), with sensitivity and specificity evaluated using DeLong’s test. Results: Random forest demonstrated the best performance in prediction considering features extracted from DWI nodules (67% of accuracy, 0.83 AUC), from T2 fat (78% of accuracy, 0.86 AUC), and from T2 glands (78% of accuracy, 0.97 AUC). The combination of the three sequences in the nodule evaluation was more accurate compared with the single sequences (88%). Combining all the nodule features with gland and PPAT features, an accuracy of 89% with AUC near 1 was obtained. Compared with the analysis of the nodule and the PPAT, the whole-gland evaluation had the best performance (p ≤ 0.05) in predicting LNS when compared with the nodule. Conclusions: Precise nodal staging is essential for PCa patients’ prognosis and therapeutic strategy. When compared with a radiologist’s assessment, radiomics models enhance the diagnostic accuracy of lymph node staging for prostate cancer. Although data are still lacking, deep learning models may be able to further improve on this. Full article

Objectives: The primary objective of this study was to identify whether patients with prostate cancer (PCa) could progress to denervation-resistant prostate cancer (CRPC) after 12 months of hormone therapy. Methods: A total of 96 PCa patients with baseline clinical data who underwent multiparametric magnetic resonance imaging (MRI) between September 2018 and September 2022 were included in this retrospective study. Patients were classified as progressing or not progressing to CRPC on the basis of their outcome after 12 months of hormone therapy. A dense multimodal fusion artificial intelligence (Dense-MFAI) model was constructed by incorporating a squeeze-and-excitation block and a spatial pyramid pooling layer into a dense convolutional network (DenseNet), as well as integrating the eXtreme Gradient Boosting machine learning algorithm. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic curves, area under the curve (AUC) and confusion matrices were used as classification performance metrics. Results: The Dense-MFAI model demonstrated an accuracy of 94.2%, with an AUC of 0.945, when predicting the progression of patients with PCa to CRPC after 12 months of hormone therapy. The experimental validation demonstrated that combining radiomics feature mapping with baseline clinical characteristics significantly improved the model’s classification performance, confirming the importance of multimodal data. Conclusions: The Dense-MFAI model proposed in this study has the ability to more accurately predict whether a PCa patient could progress to CRPC. This model can assist urologists in developing the most appropriate treatment plan and prognostic measures. Full article

Emerging imaging-guided technologies, such as prostate-specific membrane antigen radioguided surgery (PSMA-RGS) and augmented reality (AR), could enhance the precision and efficacy of robot-assisted prostate cancer (PCa) surgical approaches, maximizing the surgeons’ ability to remove all cancer sites and thus patients’ outcomes. Sentinel node biopsy (SNB) represents an imaging-guided technique that could enhance nodal staging accuracy by leveraging lymphatic mapping with tracers. PSMA-RGS uses radiolabeled tracers with the aim to improve intraoperative lymph node metastases (LNMs) detection. Several studies demonstrated its feasibility and safety, with promising accuracy in nodal staging during robot-assisted radical prostatectomy (RARP) and in recurrence setting during salvage lymph node dissection (sLND) in patients who experience biochemical recurrence (BCR) after primary treatment and have positive PSMA positron emission tomography (PET). Near-infrared PSMA tracers, such as OTL78 and IS-002, have shown potential in intraoperative fluorescence-guided surgery, improving positive surgical margins (PSMs) and LNMs identification. Finally, augmented reality (AR), which integrates preoperative imaging (e.g., multiparametric magnetic resonance imaging [mpMRI] of the prostate and computed tomography [CT]) onto the surgical field, can provide a real-time visualization of anatomical structures through the creation of three-dimensional (3D) models. These technologies may assist surgeons during intraoperative procedures, thus optimizing the balance between oncological control and functional outcomes. However, challenges remain in standardizing these tools and assessing their impact on long-term PCa control. Overall, these advancements represent a paradigm shift toward personalized and precise surgical approaches, emphasizing the integration of innovative strategies to improve outcomes of PCa patients. Full article

Focal Therapy (FT) is an emerging treatment modality for prostate cancer (PCa). Due to its novelty, the research exploring how patients should be followed-up after treatment is limited. There is currently no established role for non-prostate-specific-antigen (PSA) biomarkers and PSMA PET. However, a combination of PSA testing, multiparametric magnetic resonance imaging (mpMRI), and systematic and targeted biopsies should routinely be used for surveillance after FT. PSA values that rise 1.0 ng/mL over the nadir after twelve months or rise 1.5 ng/mL over nadir after twenty-four to thirty-six months should raise suspicion for recurrence. The standard imaging technique is mpMRI, but it can often be difficult to interpret after FT, so using a scoring system such as prostate imaging after focal ablation (PI-FAB) or the transatlantic recommendations for prostate gland evaluation with magnetic resonance imaging after focal therapy (TARGET) allows for greater consistency between readers. This review seeks to summarize the current literature regarding surveillance after FT as it relates to biomarkers, imaging, biopsies, and consensus statements. Full article

Background/Purpose: to assess the inter-reader agreement of the PIFAB (Prostate Imaging after Focal Ablation) score, a new MRI-based standardized system for evaluating post-focal therapy prostate mpMRI, among radiologists in a single large cohort of patients treated with focal therapy (HIFU) in a tertiary care referral University Hospital. Methods: In total, 68 consecutive patients who underwent HIFU were included in this single-center retrospective observational study. A total of 109 post-HIFU follow-up mpMRIs were evaluated by three radiologists with varying levels of experience (12, 8, and 3 years, respectively). All patients underwent their first follow-up mpMRI at 6 months post-treatment, with 30 patients receiving additional evaluations at 18 months and 11 at 30 months. Results: The patients had a mean age of 70.6 ± 8.31 years, a mean pre-treatment PSA (prostate-specific antigen) of 7.85 ± 1.21 ng/mL, and a mean post-treatment PSA of 4.64 ± 4.2 ng/mL. The inter-reader agreement for PI-FAB among the three radiologists showed a Gwet’s AC2 value of 0.941 (95% confidence interval: 0.904–0.978, p < 0.0001). For the most experienced radiologist, at the 6-month follow-up 64 (94.14%) patients were scored as PI-FAB 1, 1 (1.47%) as PI-FAB 2, and 3 (4.41%) as PI-FAB 3. At the 18-month and 30-month follow-ups all patients were scored as PI-FAB 1 (no suspicion of recurrence). Conclusions: Our study demonstrates excellent inter-reader agreement among radiologists with varying levels of experience, confirming that the PI-FAB score is highly reproducible when evaluating post-treatment mpMRI scans. The low rate of PI-FAB 2 and PI-FAB 3 lesions observed at the first follow-up, coupled with the absence of significant recurrence in subsequent evaluations, suggests that HIFU is a reliable technique for prostate cancer treatment in selected patients. Full article

Background: The maximum standardised uptake value (SUV_max) can potentially be affected by the uptake period during PSMA PET imaging. The optimal image acquisition period for 2-(3-{1-carboxy-5-[(6-18F-fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid (¹⁸F-DCFPyL)PSMA PET/CT is yet to be established. This study aims to evaluate the effect of the uptake period on the SUV_max in diagnosing localised, clinically significant prostate cancer using ¹⁸F-DCFPyL-PSMA PET/CT. Methods: Sixty biopsy-naive men with one or more PI-RADS 4 or 5 lesions of at least 10 mm on multiparametric MRI (mpMRI) were enrolled to undergo ¹⁸F-DCFPyL-PSMA PET/CT. SUV_max was prospectively measured following an uptake period of 60, 90 and 120 min post injection of ¹⁸F-DCFPyL-PSMA radiotracer. Concordance with biopsy results or final histopathology was recorded. Results: Mean absolute differences in SUV_max at 60 vs. 90, 60 vs. 120, and 90 vs. 120 min uptake periods were 3.23 (SD 4.76), 4.53 (SD 7.33), and 3.24 (SD 4.56), respectively. This represents a statistically significant systematic increase in SUV_max (p-value < 0.001) with increasing uptake period. The interval between the uptake period of 60 vs. 120 min represented the largest SUV_max change of 29.98%. Conclusions: The SUV_max is a dynamic variable significantly affected by uptake period. Our study supports image acquisition at 120 min following injection of ¹⁸F-DCFPyL radiotracer. Further studies are needed to determine if this acquisition period can be applied to other Fluorine-18 based PSMA radiotracers. Full article