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Constant interactions between tumor cells and the extracellular matrix (ECM) influence the progression of prostate cancer (PCa). One of the key components of the ECM are collagen fibers, since they are responsible for the tissue stiffness, growth, adhesion, proliferation, migration, invasion/metastasis, cell signaling, and immune recruitment of tumor cells. To explore this molecular marker in the content of PCa, we investigated two different tumor volumes (500 mm3 and 1000 mm3) of a xenograft mouse model of PCa with molecular magnetic resonance imaging (MRI) using a collagen-specific probe. For in vivo MRI evaluation, T1-weighted sequences before and after probe administration were analyzed. No significant signal difference between the two tumor volumes could be found. However, we detected a significant difference between the signal intensity of the peripheral tumor area and the central area of the tumor, at both 500 mm3 (p < 0.01, n = 16) and at 1000 mm3 (p < 0.01, n = 16). The results of our histologic analyses confirmed the in vivo studies: There was no significant difference in the amount of collagen between the two tumor volumes (p > 0.05), but within the tumor, higher collagen expression was observed in the peripheral area compared with the central area of the tumor. Laser ablation with inductively coupled plasma mass spectrometry further confirmed these results. The 1000 mm3 tumors contained 2.8 ± 1.0% collagen and the 500 mm3 tumors contained 3.2 ± 1.2% (n = 16). There was a strong correlation between the in vivo MRI data and the ex vivo histological data (y = −0.068x + 1.1; R2 = 0.74) (n = 16). The results of elemental analysis by inductively coupled plasma mass spectrometry supported the MRI data (y = 3.82x + 0.56; R2 = 0.79; n = 7). MRI with the collagen-specific probe in PCa enables differentiation between different tumor areas. This may help to differentiate tumor from healthy tissue, potentially identifying tumor areas with a specific tumor biology. [ABSTRACT FROM AUTHOR]

Simple Summary: Since prostate MRI is increasingly applied and yet limited by long acquisition times, we prospectively investigated the performance of a novel reconstruction algorithm combining compressed sensing, parallel imaging and deep learning (C-SENSE AI) in patients with histologically proven prostate cancer. Highly accelerated T2w images were compared to clinical standard-of-reference T2w images. C-SENSE AI enabled a 58% acceleration in T2w imaging of the prostate while obtaining significantly better image quality and tumor detection. C-SENSE AI seems particularly interesting in view of the need for accelerated prostate MRI (e.g., in screening protocols) with preserved high image quality. Background: To assess the performance of prospectively accelerated and deep learning (DL) reconstructed T2-weighted (T2w) imaging in volunteers and patients with histologically proven prostate cancer (PCa). Methods: Prospectively undersampled T2w datasets were acquired with acceleration factors of 1.7 (reference), 3.4 and 4.8 in 10 healthy volunteers and 23 patients with histologically proven PCa. Image reconstructions using compressed SENSE (C-SENSE) and a combination of C-SENSE and DL-based artificial intelligence (C-SENSE AI) were analyzed. Qualitative image comparison was performed using a 6-point Likert scale (overall image quality, noise, motion artifacts, lesion detection, diagnostic certainty); the T2 and PI-RADS scores were compared between the two reconstructions. Additionally, quantitative image parameters were assessed (apparent SNR, apparent CNR, lesion size, line profiles). Results: All C-SENSE AI-reconstructed images received a significantly higher qualitative rating compared to the C-SENSE standard images. Analysis of the quantitative parameters supported this finding, with significantly higher aSNR and aCNR. The line profiles demonstrated a significantly steeper signal change at the border of the prostatic lesion and the adjacent normal tissue in the C-SENSE AI-reconstructed images, whereas the T2 and PI-RADS scores as well as the lesion size did not differ. Conclusion: In this prospective study, we demonstrated the clinical feasibility of a novel C-SENSE AI reconstruction enabling a 58% acceleration in T2w imaging of the prostate while obtaining significantly better image quality. [ABSTRACT FROM AUTHOR]

Simple Summary: Magnetic resonance imaging (MRI) is a non-invasive method and can be used to diagnose prostate cancer (PCa). Due to their high biological safety, iron oxide nanoparticles are becoming increasingly important as contrast agents for MRI. Macrophages are able to take up these iron particles, which leads to a loss of signal in T2- and T2*-weighted images during MRI. Macrophages play an important role in the development and progression of prostate cancer. In this article, ferumoxytol is visualized at two different PCa volumes on MRI in a xenograft mouse model. Ferumoxytol is a superparamagnetic iron oxide probe and was used here as a contrast agent. The in vivo data were correlated with histological data. When using ferumoxytol, we found that small tumors took up more ferumoxytol than larger tumor volumes. These results were obtained in vivo as well as ex vivo. Prostate cancer (PCa) is one of the most common cancers in men. For detection and diagnosis of PCa, non-invasive methods, including magnetic resonance imaging (MRI), can reduce the risk potential of surgical intervention. To explore the molecular characteristics of the tumor, we investigated the applicability of ferumoxytol in PCa in a xenograft mouse model in two different tumor volumes, 500 mm3 and 1000 mm3. Macrophages play a key role in tumor progression, and they are able to internalize iron-oxide particles, such as ferumoxytol. When evaluating T2*-weighted sequences on MRI, a significant decrease of signal intensity between pre- and post-contrast images for each tumor volume (n = 14; p < 0.001) was measured. We, furthermore, observed a higher signal loss for a tumor volume of 500 mm3 than for 1000 mm3. These findings were confirmed by histological examinations and laser ablation inductively coupled plasma-mass spectrometry. The 500 mm3 tumors had 1.5% iron content (n = 14; σ = 1.1), while the 1000 mm3 tumors contained only 0.4% iron (n = 14; σ = 0.2). In vivo MRI data demonstrated a correlation with the ex vivo data (R2 = 0.75). The results of elemental analysis by inductively coupled plasma-mass spectrometry correlated strongly with the MRI data (R2 = 0.83) (n = 4). Due to its long retention time in the blood, biodegradability, and low toxicity to patients, ferumoxytol has great potential as a contrast agent for visualization PCa. [ABSTRACT FROM AUTHOR]

Purpose: This study compared 68Gallium-prostate-specific-membrane-antigen based Positron-emission-tomography (68Ga-PSMA-PET) and 99metastabletechnetium-3,3-diphospho-1,2-propanedicarbonacid (99mTc-DPD-SPECT) in performing skeletal staging in prostate cancer (PC) patients and evaluated the additional value of the information from low-dose-computed tomography (CT).Materials and Methods: In this retrospective study, 54 patients who received 68Ga-PSMA-PET/CT and 99mTc-DPD-SPECT/CT within 80 days were extracted from our database. Osseous lesions were classified as benign, malignant or equivocal. Lesion, region and patient based analysis was performed with and without CT fusion. The reference standard was generated by defining a best valuable comparator (BVC) containing information from all available data.Results: In the patient based analysis, accuracies measured as "area-under-the-curve" (AUC) for 68Ga-PSMA-PET, 99mTc-SPECT, 68Ga-PSMA-PET/CT and 99mTc-SPECT/CT were 0.97-0.96, 0.86-0.83, 1.00 and 0.83, respectively (p<0.05) (ranges = optimistic vs. pessimistic view). Region based analysis resulted in the following sensitivities and specificities: 91.8-97.7%, 100-99.5% (PET); 61.2-70.6%, 99.8-98.3% (SPECT); 97.7%, 100% (PET/CT), 69.4% and 98.3% (SPECT/CT) (p<0.05). The amount of correct classifications of equivocal lesions by CT was significantly higher in PET (100%) compared to SPECT (52.4%) (p<0.05).Conclusion: 68Ga-PSMA-PET outperforms 99mTc-DPD-SPECT in detecting bone metastases in PC patients. Additional information from low-dose-CT resulted in a significant reduction in equivocal lesions in both modalities, however 68Ga-PSMA-PET benefited most.Key Points: • Ga-PSMA-PET outperforms 99m Tc-DPD-SPECT in skeletal staging in prostate cancer patients • Proportion of equivocal decisions was significantly reduced by CT-fusion in both modalities • Ga-PSMA-PET benefits more from CT information, compared to 99m Tc-DPD-SPECT. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate potential differences in "Glu-NH-CO-NH-Lys" radio-labeled with [68Ga]gallium N,N-bis[2-hydroxy-5-(carboxyethyl)benzyl]ethylenediamine-N,N-diacetic acid ([68Ga]PSMA-HBED-CC) uptake in osteolytic, osteoblastic, mixed, and bone marrow metastases in prostate cancer (PC) patients.Procedures: This retrospective study was approved by the local ethics committee. Patients who received [68Ga]PSMA-HBED-CC positron emission tomography/computed tomography ([68Ga]PSMA-PET/CT) with at least one positive bone metastasis were included in this study. Only patients who have not received systemic therapy for their PC were included. Bone metastases had to be confirmed by at least one other imaging modality or follow-up investigation. The maximum standardized uptake value (SUVmax) and mean Hounsfield units (HUmean) of each metastasis were measured. Based on CT, each metastasis was classified as osteolytic (OL), osteoblastic (OB), bone marrow (BM), or mixed (M).Results: One hundred fifty-four bone metastases in 30 patients were evaluated. Eighty out of 154 (51.9%) metastases were classified as OB, 21/154 (13.6%) as OL, 23/154 (14.9%) as M, and 30/154 (19.5%) as BM. The SUVmax for the different types of metastases were 10.6 ± 7.07 (OB), 24.0 ± 19.3 (OL), 16.0 ± 21.0 (M), and 14.7 ± 9.9 (BM). The SUVmax of OB vs. OL and OB vs. BM metastases differed significantly (p ≤ 0.025). A significant negative correlation between HUmean and SUVmax (r = -0.23, p < 0.05) was measured.Conclusions: [68Ga]PSMA-HBED-CC uptake is higher in osteolytic and bone marrow metastases compared to osteoblastic metastases. Information derived from [68Ga]PSMA-PET and CT complement each other for the reliable diagnosis of the different types of bone metastases in PC patients. [ABSTRACT FROM AUTHOR]

Simple Summary: One of the most commonly diagnosed cancers in men is prostate cancer (PCa). Understanding tumor progression can help diagnose and treat the disease at an early stage. Components of the extracellular matrix (ECM) play a key role in the development and progression of PCa. Elastin is an essential component of the ECM and constantly changes during tumor development. This article visualizes and quantifies elastin in magnetic resonance imaging (MRI) using a small molecule probe. Results were correlated with histological examinations. Using an elastin-specific molecular probe, we were able to make predictions about the cellular structure in relation to elastin and thus draw conclusions about the size of the tumor, with smaller tumors having a higher elastin content than larger tumors. Human prostate cancer (PCa) is a type of malignancy and one of the most frequently diagnosed cancers in men. Elastin is an important component of the extracellular matrix and is involved in the structure and organization of prostate tissue. The present study examined prostate cancer in a xenograft mouse model using an elastin-specific molecular probe for magnetic resonance molecular imaging. Two different tumor sizes (500 mm3 and 1000 mm3) were compared and analyzed by MRI in vivo and histologically and analytically ex vivo. The T1-weighted sequence was used in a clinical 3-T scanner to calculate the relative contrast enhancement before and after probe administration. Our results show that the use of an elastin-specific probe enables better discrimination between tumors and surrounding healthy tissue. Furthermore, specific binding of the probe to elastin fibers was confirmed by histological examination and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). Smaller tumors showed significantly higher signal intensity (p > 0.001), which correlates with the higher proportion of elastin fibers in the histological evaluation than in larger tumors. A strong correlation was seen between relative enhancement (RE) and Elastica–van Gieson staining (R2 = 0.88). RE was related to inductively coupled plasma–mass spectrometry data for Gd and showed a correlation (R2 = 0.78). Thus, molecular MRI could become a novel quantitative tool for the early evaluation and detection of PCa. [ABSTRACT FROM AUTHOR]

Simple Summary: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an important method to analyze the perfusion model of tumors, allowing noninvasive quantification of microvascular structure and function. Furthermore, simultaneous [68Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/MRI is currently the most advantageous way for assessing prostate cancer staging. Therefore, combining these two examinations helps to diagnose the lesions more comprehensively. Our study analyzes perfusion parameters between intraprostatic lesions and the correlation between perfusion parameters and [68Ga]Ga-PSMA-11 PET. This study highlights the significant effect of PSMA uptake on perfusion parameters. We aimed to retrospectively compare the perfusion parameters measured from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of prostate benign lesions and malignant lesions to determine the relationship between perfusion parameters. DCE-MRI was performed in patients with PCa who underwent simultaneous [68Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/MRI. Six perfusion parameters (arrival time (AT), time to peak (TTP), wash-in slope (W-in), wash-out slope (W-out), peak enhancement intensity (PEI), and initial area under the 60-s curve (iAUC)), and a semi-quantitative parameter, standardized uptake values maximum (SUVmax) were calculated by placing regions of interest in the largest area of the lesions. The DCE-MRI parameters between prostate benign and malignant lesions were compared. The DCE-MRI parameters in both the benign and malignant lesions subgroup with SUVmax ≤ 3.0 and SUVmax > 3.0 were compared. The correlation of DCE-MRI parameters was investigated. Malignant lesions demonstrated significantly shorter TTP and higher SUVmax than did benign lesions. In the benign and malignant lesions subgroup, perfusion parameters of lesions with SUVmax ≤ 3.0 show no significant difference to those with SUVmax > 3.0. DCE-MRI perfusion parameters show a close correlation with each other. DCE-MRI parameters reflect the perfusion characteristics of intraprostatic lesions with malignant lesions, demonstrating significantly shorter TTP. There is a moderate to strong correlation between DCE-MRI parameters. Semi-quantitative analysis reflects that malignant lesions show a significantly higher SUVmax than benign lesions. [ABSTRACT FROM AUTHOR]

This review summarizes recent developments regarding molecular imaging markers for magnetic resonance imaging (MRI) of prostate cancer (PCa). Currently, the clinical standard includes MR imaging using unspecific gadolinium-based contrast agents. Specific molecular probes for the diagnosis of PCa could improve the molecular characterization of the tumor in a non-invasive examination. Furthermore, molecular probes could enable targeted therapies to suppress tumor growth or reduce the tumor size. [ABSTRACT FROM AUTHOR]

Simple Summary: The newest Prostate Imaging Reporting and Data System (PI-RADS) version 2.1, was published in 2019. There are a few variations of the new standard, which will change prostate lesions' classification rules. Our study aims to analyze the pattern change of lesion positron emission tomography (PET) standardized uptake values maximum (SUVmax) distribution under PI-RADS V2.1, compared with PI-RADS V2.0. Moreover, we studied the correlation between prostate-specific membrane antigen (PSMA) SUVmax and magnetic resonance imaging (MRI) PI-RADS. So far, there is no article reporting the effect of the newest PI-RADS on [68Ga]Ga-PSMA-11 PET/MRI. We did a thorough analysis, including two subgroups, peripheral zone, transitional zone, and 215 lesions. We analyzed the impact of each variation of PI-RADS one by one. Purpose: We aimed to evaluate the correlation between PSMA uptake and magnetic resonance imaging (MRI) PI-RADS of simultaneous [68Ga]Ga-PSMA-11 PET/MRI regarding PI-RADS version 2.0 and 2.1 respectively and compared the difference between these two versions. Materials and Methods: We retrospectively analyzed a total of forty-six patients with biopsy-proven prostate cancer who underwent simultaneous [68Ga]Ga-PSMA-11 PET/MRI. We classified the lesions regarding PI-RADS version 2.0 and 2.1, peripheral zone (PZ), and transitional zone (TZ), respectively. Based on regions of interest (ROI), standardized uptake values maximum (SUVmax), and corresponding lesion-to-background ratios (LBR) of SUVmax of each category, PI-RADS score 1 to 5, were measured. A comparison between PI-RADS version 2.0 and PI-RADS version 2.1 was performed. Results: A total of 215 focal prostate lesions were analyzed, including two subgroups, 125 TZ and 90 PZ. Data are reported as median and interquartile range (IQR). Regarding PI-RADS version 2.1, TZ SUVmax of each category were 1.5 (0.5, 1.9), 1.9 (0.8, 2.3), 3.3 (2.1, 4.6), 4.2 (3.1, 5.7), 7.3 (5.2, 9.7). PZ SUVmax of each category were 1.0 (0.8, 1.6), 2.5 (1.5, 3.2), 3.3 (1.9, 4.5), 4.3 (3.0, 5.4), 7.4 (5.0, 9.3). Regarding the inter-reader agreement of the overall PI-RADS assessment category, the kappa value was 0.723 for version 2.0 and 0.853 for version 2.1. Conclusion: Revisions of PI-RADS version 2.1 results in variations in lesions classification. Lesions with the PI-RADS category of 3, 4, and 5 present relatively higher intraprostatic PSMA uptake, while lesions with the PI-RADS category of 1 and 2 present relatively lower and similar uptake. Version 2.1 has higher inter-reader reproducibility than version 2.0. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]