Prostate Cancer Imaging Research Articles

Two Novel [68Ga]Ga-Labeled Radiotracers Based on Metabolically Stable [Sar11]RM26 Antagonistic Peptide for Diagnostic Positron Emission Tomography Imaging of GRPR-Positive Prostate Cancer.

Gastrin releasing peptide receptor (GRPR) is overexpressed in prostate cancer (PC-3) and can be used for diagnostic purposes. We herein present the design and preclinical evaluation of two novel NOTA/NODAGA-containing peptides suitable for labeling with the positron emission tomography (PET) radionuclide Ga-68. These analogs are based on the previously reported GRPR-antagonist DOTAGA-PEG2-[Sar11]RM26, developed for targeted radiotheraostic applications. Both NOTA-PEG2-[Sar11]RM26 and NODAGA-PEG2-[Sar11]RM26 were successfully labeled with Ga-68 and evaluated in vitro and in vivo using PC-3 cell models. Both, [68Ga]Ga-NOTA-PEG2-[Sar11]RM26 and [68Ga]Ga-NODAGA-PEG2-[Sar11]RM26 displayed high metal-chelate stability in phosphate buffered saline and against the EDTA-challenge. The two [68Ga]Ga-labeled conjugates demonstrated highly GRPR-mediated uptake in vitro and in vivo and exhibited a slow internalization over time, typical for radioantagonistis. The [natGa]Ga-loaded peptides displayed affinity in the low nanomole range for GRPR in competition binding experiments. The new radiotracers demonstrated biodistribution profiles suitable for diagnostic imaging shortly after administration with fast background clearance. Their high tumor uptake (13 ± 1 and 15 ± 3% IA/g for NOTA and NODAGA conjugates, respectively) and high tumor-to-blood ratios (60 ± 10 and 220 ± 70, respectively) 3 h pi renders them promising PET tracers for use in patients. Tumor-to-normal organ ratios were higher for [68Ga]Ga-NODAGA-PEG2-[Sar11]RM26 than for the NOTA-containing counterpart. The performance of the two radiopeptides was further supported with the PET/CT images. In conclusion, [68Ga]Ga-NODAGA-PEG2-[Sar11]RM26 is a promising PET imaging tracer for visualization of GRPR-expressing lesions with high imaging contrast shortly after administration.

Preparation, Biological Evaluation, and First-in-Human Single-Photon Emission Computed Tomography (SPECT) Study of 99mTc-Labeled Prostate-Specific Membrane Antigen (PSMA)-Targeted Radiotracers Containing Triazole with Reduced Kidneys Accumulation.

Prostate-specific membrane antigen (PSMA), a well-established biological marker for prostate cancer (PCa) imaging and therapy, is overexpressed on the surface of prostate cancer lesions. In this study, a triazole ring was introduced into the linker by click chemistry to generate a HYNIC-derived ligand (T), which exhibited good PSMA affinity (Ki = 2.23 nM). Eight stable 99mTc-labeled complexes, [99mTc]Tc-T-Mn (n = 1-8), with hydrophilic properties were synthesized by incorporating different coligands at high radiochemical yields and purities without purification. The radioligands were concentrated in the kidneys of healthy Kunming male mice and were significantly blocked by the PSMA inhibitor ZJ-43. The uptake of the optimized complex [99mTc]Tc-T-M2 was correlated with PSMA, and it had good PSMA affinity (Kd = 5.42 nM). [99mTc]Tc-T-M2 accumulated on LNCaP (PSMA++) tumors and was significantly blocked by ZJ-43 at 2 h p.i., indicating high PSMA specificity. Relatively suitable kidney uptake was beneficial for reducing kidneys exposure in patients. SPECT/CT imaging of [99mTc]Tc-T-M2 in LNCaP (PSMA++) or 22Rv1 (PSMA+) tumor-bearing mice revealed high tumor uptake, low background uptake (especially low kidney uptake (49.06 ± 9.20 %ID/g) at 2 h p.i.), and obvious inhibition by ZJ-43, whereas PC-3 (PSMA-) tumors were undetectable. A freeze-dried [99mTc]Tc-T-M2 kit was successfully developed (T-M2 kit). Preliminary clinical trials showed that [99mTc]Tc-T-M2 clearly identified small prostate cancer lesions and has potential for clinical application.

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

Advances in the Development of Positron Emission Tomography Tracers for Improved Detection of Differentiated Thyroid Cancer.

Thyroid cancer poses a significant challenge in clinical management, necessitating precise diagnostic tools and treatment strategies for optimal patient outcomes. This review explores the evolving field of radiotracers in the diagnosis and management of thyroid cancer, focusing on prostate-specific membrane antigen (PSMA)-based radiotracers, fibroblast activation protein inhibitor (FAPI)-based radiotracers, Arg-Gly-Asp (RGD)-based radiotracers, and 18F-tetrafluoroborate (18F-TFB). PSMA-based radiotracers, initially developed for prostate cancer imaging, have shown promise in detecting thyroid cancer lesions; however, their detection rate is lower than 18F-FDG PET/CT. FAPI-based radiotracers, targeting fibroblast activation protein highly expressed in tumors, offer potential in the detection of lymph nodes and radioiodine-resistant metastases. RGD-based radiotracers, binding to integrin αvβ3 found on tumor cells and angiogenic blood vessels, demonstrate diagnostic accuracy in detecting radioiodine-resistant thyroid cancer metastases. 18F-TFB emerges as a promising PET tracer for imaging of lymph node metastases and recurrent DTC, offering advantages over traditional methods. Overall, these radiotracers show promise in enhancing diagnostic accuracy, patient stratification, and treatment selection in differentiated thyroid cancer, warranting further research and clinical validation. Given the promising staging capabilities of 18F-TFB and the efficacy of FAP-targeting tracers in advanced, potentially dedifferentiated cases, continued investigation in these domains is justified.

Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer

Multiple strategies integrating magnetic resonance imaging (MRI) and clinical data have been proposed to determine the need for a prostate biopsy in men with suspected clinically significant prostate cancer (csPCa) (Gleason score ≥3 + 4). However, inconsistencies across different strategies create challenges for drawing a definitive conclusion. To determine the optimal prostate biopsy decision-making strategy for avoiding unnecessary biopsies and minimizing the risk of missing csPCa by combining MRI Prostate Imaging Reporting & Data System (PI-RADS) and clinical data. PubMed, Ovid MEDLINE, Embase, Web of Science, and Cochrane Library from inception to July 1, 2022. English-language studies that evaluated men with suspected but not confirmed csPCa who underwent MRI PI-RADS followed by prostate biopsy were included. Each study had proposed a biopsy plan by combining PI-RADS and clinical data. Studies were independently assessed for eligibility for inclusion. Quality of studies was appraised using the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the Newcastle-Ottawa Scale. Mixed-effects meta-analyses and meta-regression models with multimodel inference were performed. Reporting of this study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Independent risk factors of csPCa were determined by performing meta-regression between the rate of csPCa and PI-RADS and clinical parameters. Yields of different biopsy strategies were assessed by performing diagnostic meta-analysis. The analyses included 72 studies comprising 36 366 patients. Univariable meta-regression showed that PI-RADS 4 (β-coefficient [SE], 7.82 [3.85]; P = .045) and PI-RADS 5 (β-coefficient [SE], 23.18 [4.46]; P < .001) lesions, but not PI-RADS 3 lesions (β-coefficient [SE], -4.08 [3.06]; P = .19), were significantly associated with a higher risk of csPCa. When considered jointly in a multivariable model, prostate-specific antigen density (PSAD) was the only clinical variable significantly associated with csPCa (β-coefficient [SE], 15.50 [5.14]; P < .001) besides PI-RADS 5 (β-coefficient [SE], 9.19 [3.33]; P < .001). Avoiding biopsy in patients with lesions with PI-RADS category of 3 or less and PSAD less than 0.10 (vs <0.15) ng/mL2 resulted in reducing 30% (vs 48%) of unnecessary biopsies (compared with performing biopsy in all suspected patients), with an estimated sensitivity of 97% (vs 95%) and number needed to harm of 17 (vs 15). These findings suggest that in patients with suspected csPCa, patient-tailored prostate biopsy decisions based on PI-RADS and PSAD could prevent unnecessary procedures while maintaining high sensitivity.

Use of multiparametric magnetic resonance imaging in prostate cancer: A review

Prostate cancer, or PCa, is a prominent male malignancy. For men with prostate cancer, accurate staging is essential for planning treatment and determining the prognosis. The way prostate cancer is currently diagnosed has led to two types of problems: overdiagnosis, which results in overtreatment, and underdiagnosis, which leads to missed diagnoses. Multiparametric magnetic resonance imaging (mpMRI) could assist in reducing prostate cancer diagnosis errors. Automatic prostate cancer techniques often use deep learning or machine learning to identify the lesion or tumor. Even after using these methods, they are not accurate every time in detecting and identifying prostate tumors after giving multiple sequences of mpMRI as input. Due to the absence of a clinically established test dataset, the output of the automatic prostate cancer system is extremely hard to verify. With the help of Explainable Artificial Intelligence (XAI) and expert review, the results of automatic prostate cancer techniques can be verified.

Key learnings from concordant systematic biopsies in prostate-specific membrane antigen positron emission tomography/computed tomography-guided prostate biopsies: Enhancing targeting accuracy.

Prostate cancer (PCa) diagnosis and staging have evolved with the advent of 68Ga-Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA-PET/CT). This study investigates the role of complementary systematic biopsies (SB) during PSMA-PET/CT-guided targeted prostate biopsies (PET-TB) for PCa detection, grading, and distribution. We address the uncertainty surrounding the necessity of SB in conjunction with PET-TB. We analyzed PCa grading and distribution in 30 men who underwent PET-TB and SB because of contraindication to magnetic resonance imaging or high clinical suspicion of PCa. Tumor distribution was assessed in relation to the PET-highlighted lesions. Standardized reporting schemes, encompassing SUVmax, PRIMARY score, and miTNM classification, were evaluated. 80% of patients were diagnosed with PCa, with 70% classified as clinically significant (csPCa). SB detected more csPCa cases than PET-TB, but the differences were not statistically significant. Discordant results were observed in 25% of cases, where SB outperformed PET-TB. Spatial analysis revealed that tumor-bearing cores from SB were often located in close proximity to the PET-highlighted region. Reporting schemes showed potential for csPCa detection with significantly increased SUVmax in csPCA patients. Subsequent follow-up data underscored the importance of SB in precise PCa grading and staging. While PET-TB can simplify prostate biopsy and reduce invasiveness by core number, SB cannot be omitted yet due to potential PET-TB targeting errors. Factors such as limited spatial resolution and fusion inaccuracies contribute to the need for SB. Standardization in reporting schemes currently cannot compensate for targeting errors highlighting the need for refinement.

The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer.

Molecular imaging is a key tool in the diagnosis and treatment of prostate cancer (PCa). Magnetic Resonance (MR) plays a major role in this respect with nuclear medicine imaging, particularly, Prostate-Specific Membrane Antigen-based, (PSMA-based) positron emission tomography with computed tomography (PET/CT) also playing a major role of rapidly increasing importance. Another key technology finding growing application across medicine and specifically in molecular imaging is the use of machine learning (ML) and artificial intelligence (AI). Several authoritative reviews are available of the role of MR-based molecular imaging with a sparsity of reviews of the role of PET/CT. This review will focus on the use of AI for molecular imaging for PCa. It will aim to achieve two goals: firstly, to give the reader an introduction to the AI technologies available, and secondly, to provide an overview of AI applied to PET/CT in PCa. The clinical applications include diagnosis, staging, target volume definition for treatment planning, outcome prediction and outcome monitoring. ML and AL techniques discussed include radiomics, convolutional neural networks (CNN), generative adversarial networks (GAN) and training methods: supervised, unsupervised and semi-supervised learning.

Imaging classification of prostate cancer with extracapsular extension and its impact on positive surgical margins after laparoscopic radical prostatectomy.

To explore the impact of different imaging classifications of prostate cancer (PCa) with extracapsular extension (EPE) on positive surgical margins (PSM) after laparoscopic radical prostatectomy. Clinical data were collected for 114 patients with stage PT3a PCa admitted to Ningbo Yinzhou No. 2 Hospital from September 2019 to August 2023. Radiologists classified the EPE imaging of PCa into Type I, Type II, and Type III. A chi-square test or t-test was employed to analyze the factors related to PSM. Multivariate regression analysis was conducted to determine the factors associated with PSM. Receiver operating characteristic curve analysis was used to calculate the area under the curve and evaluate the diagnostic performance of our model. Clinical decision curve analysis was performed to assess the clinical net benefit of EPE imaging classification, biopsy grade group (GG), and combined model. Among the 114 patients, 58 had PSM, and 56 had negative surgical margins. Multivariate analysis showed that EPE imaging classification and biopsy GG were risk factors for PSM after laparoscopic radical prostatectomy. The areas under the curve for EPE imaging classification and biopsy GG were 0.677 and 0.712, respectively. The difference in predicting PSM between EPE imaging classification and biopsy GG was not statistically significant (P>0.05). However, when used in combination, the diagnostic efficiency significantly improved, with an increase in the area under the curve to 0.795 (P<0.05). The clinical decision curve analysis revealed that the clinical net benefit of the combined model was significantly higher than that of EPE imaging classification and biopsy GG. EPE imaging classification and biopsy GG were associated with PSM after laparoscopic radical prostatectomy, and their combination can significantly improve the accuracy of predicting PSM.

Using a deep learning prior for accelerating hyperpolarized 13C MRSI on synthetic cancer datasets.

We aimed to incorporate a deep learning prior with k-space data fidelity for accelerating hyperpolarized carbon-13 MRSI, demonstrated on synthetic cancer datasets. A two-site exchange model, derived from the Bloch equation of MR signal evolution, was firstly used in simulating training and testing data, that is, synthetic phantom datasets. Five singular maps generated from each simulated dataset were used to train a deep learning prior, which was then employed with the fidelity term to reconstruct the undersampled MRI k-space data. The proposed method was assessed on synthetic human brain tumor images (N = 33), prostate cancer images (N = 72), and mouse tumor images (N = 58) for three undersampling factors and 2.5% additive Gaussian noise. Furthermore, varied levels of Gaussian noise with SDs of 2.5%, 5%, and 10% were added on synthetic prostate cancer data, and corresponding reconstruction results were evaluated. For quantitative evaluation, peak SNRs were approximately 32 dB, and the accuracy was generally improved for 5 to 8 dB compared with those from compressed sensing with L1-norm regularization or total variation regularization. Reasonable normalized RMS error were obtained. Our method also worked robustly against noise, even on a data with noise SD of 10%. The proposed singular value decomposition + iterative deep learning model could be considered as a general framework that extended the application of deep learning MRI reconstruction to metabolic imaging. The morphology of tumors and metabolic images could be measured robustly in six times acceleration using our method.

Abstract A010: Prostate-specific membrane antigen use in glioma management: past, present, and future

Abstract Introduction: Prostate-Specific Membrane Antigen (PSMA) is a type II membrane-bound zinc metallopeptidase expressed in various tissues, including the prostate, renal tubular epithelium, small and large intestinal mucosa, and brain. It plays a role in cell proliferation pathways and folate and glutamate metabolism. PSMA has been utilized for imaging and treatment of prostate cancer and is also expressed in solid tumor neovasculature of other cancers. Gliomas, which are central nervous system neoplasms of glial tissue, represent a challenging group of tumors with limited treatment options due to their invasive nature. PSMA's ability to internalize and location makes it a promising diagnostic and therapeutic target for gliomas. This review synthesizes the literature surrounding the use of PSMA in gliomas to inform current and future directions of study. Methods: A review of the literature was conducted using PubMed and Scopus databases in June 2023. Seventy-one relevant studies, including histopathological, imaging, and therapeutic investigations, were identified. These publications were categorized by year of publication to analyze the evolution of PSMA research in glioma management. Additionally, clinicaltrials.gov was searched for ongoing clinical trials involving PSMA and gliomas. Results: Histopathological studies have demonstrated PSMA's high expression in glioma vasculature, particularly in glioblastoma (GBM), a high-grade glioma (HGG). Studies have investigated PSMA's role in tumor metabolism and its interplay with other tumor markers. Some research suggests that high PSMA expression in GBM endothelium may promote angiogenesis and correlates with poor prognosis. PSMA PET imaging has shown promise in diagnosing and differentiating HGGs and low-grade gliomas (LGGs). Studies have reported high sensitivity and diagnostic accuracy of PSMA PET for HGGs, making it a potentially useful screening tool for radioligand therapy patient selection. Mouse models have also been employed to evaluate the utility of PSMA PET imaging in GBM, with some studies suggesting its application in defining non-enhancing portions of tumors and recurrence volume. PSMA-targeted therapies, particularly PSMA-targeted radiotherapy using radionuclide agents like 177Lu-PSMA-617, have been explored for the treatment of gliomas. Case reports and preliminary studies have demonstrated potential efficacy and tumor response to such therapies, warranting further investigation. Conclusion: The evolving literature indicates that PSMA holds promise as a valuable tool in the diagnosis, prognosis, and treatment of gliomas. Studies have highlighted PSMA PET imaging's high diagnostic accuracy and its potential in patient selection for targeted therapies. However, more research is needed to fully understand the role of PSMA in glioma behavior and to optimize treatment strategies. Ongoing clinical trials and future investigations will further our knowledge of PSMA's potential in managing gliomas and improving patient outcomes. Citation Format: Joshua D. McBriar, Neeva Shafiian, Steven Scharf, A. Gabriella Wernicke. Prostate-specific membrane antigen use in glioma management: past, present, and future [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr A010.

Strength through unity: Alkaline phosphatase-responsive AIEgen nanoprobe for aggregation-enhanced multi-mode imaging and photothermal therapy of metastatic prostate cancer

Strength through unity: Alkaline phosphatase-responsive AIEgen nanoprobe for aggregation-enhanced multi-mode imaging and photothermal therapy of metastatic prostate cancer

Predictive Value of Multiparametric Magnetic Resonance Imaging in Risk Group Stratification of Prostate Adenocarcinoma

The aim of this study was to further assess the clinical utility of multiparametric magnetic resonance imaging (MP-MRI) in prostate cancer (PC) staging following 2023 clinical guideline changes, both as an independent predictor of high-stage (>T3a) or high-risk PC and when combined with patient characteristics. The present study was a retrospective review of 171 patients from 2008 to 2018 who underwent MP-MRI before radical prostatectomy at a single institution. The accuracy of clinical staging was compared between conventional staging and MP-MRI-based clinical staging. Sensitivity, specificity, positive predictive value, and negative predictive value were compared, and receiver operating characteristic curves were generated. Linear regression analyses were used to calculate concordance (C-statistic). Of the 171 patients, final pathology revealed 95 (55.6%) with T2 disease, 62 (36.3%) with T3a disease, and 14 (8.2%) with T3b disease. Compared with conventional staging, MP-MRI-based staging demonstrated significantly increased accuracy in identifying T3a disease, intermediate risk, and high/very-high-risk PC. When combined with clinical characteristics, MP-MRI-based staging improved the area under the curve from 0.753 to 0.808 (P = .0175), compared with conventional staging. MP-MRI improved the identification of T3a PC, intermediate-risk PC, and high- or very-high-risk PC. Further, when combined with clinical characteristics, MP-MRI-based staging significantly improved risk stratification, compared with conventional staging. These findings represent further evidence to support the integration of MP-MRI into prostate adenocarcinoma clinical staging guidelines.

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset.

We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in images of colon, breast, and prostate cancer stained with CD3 and CD8 immunohistochemistry. Differently from other challenges setup in medical image analysis, LYSTO participants were solely given a few hours to address this problem. In this paper, we describe the goal and the multi-phase organization of the hackathon; we describe the proposed methods and the on-site results. Additionally, we present post-competition results where we show how the presented methods perform on an independent set of lung cancer slides, which was not part of the initial competition, as well as a comparison on lymphocyte assessment between presented methods and a panel of pathologists. We show that some of the participants were capable to achieve pathologist-level performance at lymphocyte assessment. After the hackathon, LYSTO was left as a lightweight plug-and-play benchmark dataset on grand-challenge website, together with an automatic evaluation platform.

Retraction: current role of multiparametric magnetic resonance imaging for prostate cancer.

[This retracts the article DOI: 10.3978/j.issn.2223-4292.2015.10.08.].

The Role of Radiation Therapy in the Management of Prostate Cancer and Posttreatment Imaging Appearances

AbstractProstate cancer remains a significant global health concern, necessitating continuous research and innovation in treatment modalities. This review explores the currently employed techniques in radiation dose planning and tumor irradiation in the context of prostate cancer management. In addition, we delve into the nuances of expected posttreatment magnetic resonance imaging (MRI) appearances within the gland or in the prostate bed, postradiation tumor recurrence, and its mimics.Radiation therapy (RT) has evolved as a cornerstone in prostate cancer treatment, offering both curative and palliative solutions. Recent developments have seen the emergence of advanced techniques such as intensity-modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT), allowing for precise targeting of cancer cells while minimizing damage to surrounding healthy tissue.The avoidance of normal tissue dose through more conformal dose distribution as in IMRT or proton therapy, improved imaging modalities as in multiparametric magnetic resonance imaging (mpMRI) and prostate positron emission tomography (PET), interventional separation of critical structures from the prostate target, and many other techniques can greatly reduce the side effects of RT. These advancements enhance treatment efficacy and reduce the risk of side effects, promoting improved patient outcomes.

Geometric distortion caused by metallic femoral head prosthesis in prostate cancer imaging on an MR Linac: in-vivo measurements of spatial deformation.

Metallic implants cause artefacts and distortion on MRI. To ensure accurate dose delivery and plan adaptation on an MR Linac, there is a need to evaluate distortion caused. Participants were imaged on an MR Linac (Elekta Unity, Elekta AB Stockholm). Three sequences were evaluated. Two vendor supplied (T2W TSE 3D), and one T2W TSE 3D optimized to reduce metal artefact distortions. Images were rigidly registered to CT images by a single observer, using bony anatomy. Three coronal and three axial images were selected, and six paired, adjacent, bony landmarks were identified on each slice. Images bisecting treatment isocentre were included. Difference between landmark coordinates was taken to be measure of distortion. Five observers participated. Thirty six pairs of bony landmarks were identified. Median difference in position of landmarks was ≤3 mm (range 0.3-4.4 mm). One-way analysis of variance (ANOVA) between observer means showed no significant variation between sequences or patients (P = 1.26 in plane, P = 0.11 through plane). Interobserver intra class correlation (ICC) was 0.70 in-plane and 0.78 through-plane. Intra-observer ICC for three observers was 0.76, 0.81, 0.83, showing moderate to good reliability on this small cohort. This in-vivo feasibility study suggests distortion due to metallic hip prosthesis is not an obstacle for pelvic radiotherapy on an MR Linac. Research on the impact on plan quality is warranted. This work supports feasibility of treating patients with metallic hip prosthesis on an MR Linac.

Prostate-Specific Membrane Antigen PET/CT Detection of Prostate Cancer Metastasis to Thyroid and Cricoid Cartilages.

Prostate-specific membrane antigen (PSMA) PET/CT has revolutionized the imaging of prostate cancer. Historically, prostate cancer metastasis to thyroid and cricoid cartilages was thought to be exceedingly rare, with only a few reported cases in the literature. Prostate cancer metastasis to the laryngeal cartilages was detected in 4 of 221 patients who underwent imaging with 18 F-PSMA (Pylarify) or 68 Ga-PSMA (Illuccix) PET/CT for initial staging of high-risk prostate cancer or restaging evaluation in the setting of biochemical recurrence from April 2022 through October 2023. The increased sensitivity and specificity of PSMA PET/CT allow for the detection of previously occult metastatic disease.

Testicular Incidentaloma on 18F-choline PET/CT in a Patient with Prostatic Adenocarcinoma.

Prostatic adenocarcinoma is characterized by elevated phosphatidylcholine metabolism. 18F-choline positron emission tomography/computed tomography (PET/CT) is widely used for patients with biochemical recurrence and a prostate-specific antigen threshold above 2 ng/mL. We report a case of a patient with high-risk prostatic adenocarcinoma undergoing 18F-choline PET/CT for biochemical recurrence. In addition to hypermetabolic abdominal lymph nodes, an unexpected right testicular hypermetabolism was observed. Such findings on 18F-choline PET/CT may suggest a primary tumor or testicular metastasis of prostate cancer. Bilateral orchiectomy revealed a vitelline tumor associated with known primary prostatic cancer. The incidental discovery of a testicular vitelline tumor during prostate cancer imaging is rare, highlighting the importance of thorough diagnostics. This case underscores the need for comprehensive care in managing complex and atypical cancer cases, emphasizing the potential for unrelated tumor discoveries during diagnostic workup. Further research is essential for a better understanding of these rare co-occurring cancers and their treatment implications.

Novel estrogen receptor β/histone deacetylase dual-targeted near-infrared fluorescent probes as theranostic agents for imaging and treatment of prostate cancer

Estrogen receptor (ER) β and histone deacetylases (HDACs), when overexpressed, are associated closely with the occurrence and development of prostate cancer and are, therefore, considered important targets and biomarkers used in the clinical treatment of prostate cancer. The present study involved the design and synthesis of the first ERβ and HDAC dual-target near-infrared fluorescent probe with both imaging capacity and antitumor activity for prostate cancer. Both P1 and P2 probes exhibited excellent ERβ selectivity, with P1 being almost exclusively selective for ERβ compared to ERα. In addition, P1 exhibited good optical properties, such as strong near-infrared emission, large Stokes shift, and better anti-interference ability, along with excellent imaging ability for living cells. P1 also exhibited potent inhibitory activity against HDAC6 and DU-145 cells, with IC50 values of 52 nM and 0.96 μM, respectively. Further, P1 was applied successfully for the in vivo imaging of prostate cancer in a mouse model, and significant in vivo antitumor efficacy was achieved. The developed dual-target NIR fluorescent probe is expected to serve as an effective tool in the research on prostate cancer, leading to novel insights for the theranostic study of diseases related to ERβ and HDACs.