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Integration of PSMA-targeted PET imaging into the armamentarium for detecting clinically significant prostate cancer
摘要： To explore the current state of using prostate-specific membrane antigen (PSMA)-targeted PET imaging to aid in the diagnosis of clinically significant prostate cancer. Prostate-specific antigen screening remains controversial, as it is associated with the underdetection of clinically significant prostate cancer as well as the overdetection and subsequent overtreatment of clinically insignificant disease. A diagnostic test that can accurately assess the presence of clinically significant prostate cancer and avoid detection of low-risk tumors is needed. Multiparametric magnetic resonance imaging (mpMRI) can aid in the detection of clinically significant prostate cancer and can be used with fusion-based biopsy platforms to target biopsies to specific lesions. However, there are several limitations of mpMRI including a modest negative predictive value for high-grade cancer. PSMA-targeted PET imaging has shown promise as a noninvasive test to aid in the detection of clinically significant prostate cancer while providing anatomical information to guide targeted biopsies. PSMA-targeted PET in combination with mpMRI offers a higher degree of diagnostic accuracy for imaging localized prostate cancer than either modality alone. PSMA-targeted PET imaging can aid in the identification of men with clinically significant prostate cancer. Further research is needed to determine the full potential of PSMA-targeted imaging in both the detection and treatment of localized prostate cancer.
关键词： focal therapy,MRI/ultrasound fusion,prostate-specific membrane antigen,prostate cancer,targeted biopsy
更新于2025-09-10 09:29:36
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - A Novel ADCs-Based CNN Classification System for Precise Diagnosis of Prostate Cancer
摘要： This paper addresses the issue of early diagnosis of prostate cancer from diffusion-weighted magnetic resonance imaging (DWI) using a convolutional neural network (CNN) based computer-aided diagnosis (CAD) system. The proposed CNN-based CAD system first segments the prostate using a geometric deformable model. The evolution of this model is guided by a stochastic speed function that exploits first-and second-order appearance models besides shape prior. The fusion of these guiding criteria is accomplished using a nonnegative matrix factorization (NMF) model. Then, the apparent diffusion coefficients (ADCs) within the segmented prostate are calculated at each b-value. They are used as imaging markers for the blood diffusion of the scanned prostate. For the purpose of classification/diagnosis, a three dimensional CNN has been trained to extract the most discriminatory features of these ADC maps for distinguishing malignant from benign prostate tumors. The performance of the proposed CNN-based CAD system is evaluated using DWI datasets acquired from 45 patients (20 benign and 25 malignant) at seven different b-values. The acquisition of these DWI datasets is performed using two different scanners with different magnetic field strengths (1.5 Tesla and 3 Tesla). The conducted experiments on in-vivo data confirm that the use of ADCs makes the proposed system nonsensitive to the magnetic field strength.
关键词： Prostate Cancer,Convolutional Neural Networks,Apparent Diffusion Coefficients
更新于2025-09-10 09:29:36
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A Sample-to-Targeted Gene Analysis Biochip for Nanofluidic Manipulation of Solid-Phase Circulating Tumor Nucleic Acid Amplification in Liquid Biopsies
摘要： The use of circulating tumor nucleic acids (ctNA) in patient liquid biopsies for targeted genetic analysis is rapidly increasing in clinical oncology. Still, the call for an integrated methodology that is both rapid and sensitive for analyzing trace ctNA amount in liquid biopsies, has unfortunately not been fully realized. Herein, we performed complex liquid biopsy sample-to-targeted genetic analysis on a biochip with 50 copies-detection limit within 30 min. Our biochip uniquely integrated: 1) electrical lysis and release of cellular targets with minimal processing; 2) nanofluidic manipulation to accelerate molecular kinetics of solid-phase isothermal amplification; 3) single-step capture and amplification of multiple NA targets prior to nanozyme-mediated electrochemical detection. Using prostate cancer liquid biopsies, we successfully demonstrated multifunctionality for cancer risk prediction; correlation of serum and urine analyses; and cancer relapse monitoring.
关键词： solid-phase amplification,microfluidics,risk stratification,liquid biopsy,prostate cancer
更新于2025-09-10 09:29:36
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Deep transfer learning-based prostate cancer classification using 3 Tesla multi-parametric MRI
摘要： Purpose The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prostate cancer (PCa) lesions and to compare the DTL-based model with a deep learning (DL) model without transfer learning and PIRADS v2 score on 3 Tesla multi-parametric MRI (3T mp-MRI) with whole-mount histopathology (WMHP) validation. Methods With IRB approval, 140 patients with 3T mp-MRI and WMHP comprised the study cohort. The DTL-based model was trained on 169 lesions in 110 arbitrarily selected patients and tested on the remaining 47 lesions in 30 patients. We compared the DTL-based model with the same DL model architecture trained from scratch and the classification based on PIRADS v2 score with a threshold of 4 using accuracy, sensitivity, specificity, and area under curve (AUC). Boot-strapping with 2000 resamples was performed to estimate the 95% confidence interval (CI) for AUC. Results After training on 169 lesions in 110 patients, the AUC of discriminating indolent from clinically significant PCa lesions of the DTL-based model, DL model without transfer learning and PIRADS v2 score C 4 were 0.726 (CI [0.575, 0.876]), 0.687 (CI [0.532, 0.843]), and 0.711 (CI [0.575, 0.847]), respectively, in the testing set. The DTL-based model achieved higher AUC compared to the DL model without transfer learning and PIRADS v2 score C 4 in discriminating clinically significant lesions in the testing set. Conclusion The DeLong test indicated that the DTL-based model achieved comparable AUC compared to the classification based on PIRADS v2 score (p = 0.89).
关键词： Whole-mount histopathology,Multi-parametric MRI,Prostate cancer,Deep learning,Clinically significant lesion classification,PIRADS v2 score
更新于2025-09-10 09:29:36
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[ACM Press the 2nd International Conference - Las Vegas, NV, USA (2018.08.27-2018.08.29)] Proceedings of the 2nd International Conference on Vision, Image and Signal Processing - ICVISP 2018 - Automatic 3D Prostate Image Segmentation via Patch-based Density Constraints Clustering
摘要： Currently methods on prostate segmentation barely solve the problems about the low prostate CT contrast, high edge ambiguity, surrounding adhesion tissues and especially the tumor motion. To effectively manage those problems in prostate treatment using CT guided radiotherapy, automated segmentation needs to be performed. In this paper, an automatic 3D prostate image segmentation via Patch-based density constraints clustering (PDCC) is developed. The main contributions of this method lie in the following three strategies: 1) compared with only using pixel intensity information, Superpixel-based 3D patch includes more structure contexts to deal with low contrast problem in prostate CT images. 2) Compacting and extracting discriminative information in the each patch with 3D gray-gradient co-occurrence matrix are used to distinguish tiny texture difference between prostate and non-prostate. 3) Density constraints clustering algorithm focus on a higher density than their neighbors’ points with relatively small distance to cope with two nearby organs touch together. Further, clusters are recognized regardless of their shape and of the dimensionality of the space in which they are embedded. The proposed method has been evaluated on 10 patients’ prostate CT image database where each patient includes 50 treatment images, and several state-of-the-art prostate CT segmentation algorithms with various evaluation metrics have been as comparisons. Experimental results demonstrate that the proposed method achieves higher segmentation accuracy and lower average surface distance.
关键词： Prostate,Segmentation,CT Image,Superpixels
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Kiev (2018.4.24-2018.4.26)] 2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) - Mueller Matrix Polarimetric Imaging of Prostate Tissue
摘要： Polarimetric imaging technique is a beneficial and non-destructive tool for probing the structural properties of different tissues. The obtained optical signature matrix will help clinicians to evaluate the condition of tissues. As the polarimetric properties of tissues are dependent to the structure and cellular skeleton, time lapsing may introduce variation in the polarization properties. Based on this, in the current study we have investigated the polarization properties of human prostate tissue over time. In this regard we have used polarization imaging technique based on Mueller matrix imaging and polar decomposition of Mueller matrix for extraction of polarization indicators. The tests have been performed for sample tissues immediately after surgery, and at intermittent intervals. The polarization properties have been re-measured, to follow the changes in the polarization properties of tissue over the time. The results of our study indicate that the diattenuation increases and depolarization decreases over time which can be associated with the structural properties of tissue accordingly.
关键词： Biomedical Imaging,Mueller matrix imaging,Polarization imaging,Prostate Tissue
更新于2025-09-10 09:29:36
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Past and Present of Imaging Modalities Used for Prostate Cancer Diagnosis: Androgen Receptor Targeted Imaging of Prostate Cancer as a Future Modality for Early, Rapid and Efficient Diagnosis
摘要： Background: Prostate cancer is the second most prevailing cancer among men worldwide. In the most cases, prostate cancer is slowly progressing, whereas, in some cases, it is a rapidly progressing disease leading to the significantly high mortality rate. Thus, there is still demand for prostate-specific imaging in order to provide image-guided early diagnosis and for the provision of patient-specific therapy. Discussion: Besides discussing traditional diagnostic approaches, this review illustrates a perspective on prostate cancer imaging summarizing current imaging approaches with a special focus on Prostate Specific Membrane Antigen (PSMA), Bombesin (BN) and Androgen Receptor (AR) targeted imaging using Positron Emission Tomography (PET) and Single Positron Emission Computed Tomography (SPECT) based on 99mTc and other radiotracers. Here, the prostate biology is reconsidered for nuclear imaging as future modality for early, rapid and efficient diagnosis of prostate cancer. Conclusion: Future direction in prostate cancer imaging involves the development of androgen receptor based imaging using nonsteroidal antiandrogen agent for early diagnosis of prostate cancer.
关键词： single photon emission computed tomography,Prostate cancer,patient-specific therapy,radiotracer,positron-emission tomography,prostate-specific membrane antigen
更新于2025-09-09 09:28:46
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Assessment of 68Ga-PSMA-11 PET positivity predictive factors in prostate cancer
摘要： Purpose: Positron emission tomography (PET) studies with 68Ga-PSMA-11 (68Ga-HBED-CC-PSMA) have earned the attention of researchers, due to overexpression of PSMA in the tumoral tissues of prostate cancer. Our aim was to analyze the potential benefit of this radiotracer in the biochemical relapse of prostate cancer. Material and methods: This retrospective analysis included 53 studies, performed on 50 male prostate cancer patients referred due to biochemical recurrence. In all cases, previous imaging techniques were negative or inconclusive. Results: Of the 53 studies, 36 (68%) were positive. Significant differences were found between the positive and negative PET groups in Gleason’s scale, PSA levels, PSAdt, late acquisition and the administration of androgen deprivation therapy during treatment (p < .05). Regarding PSA levels, 10 (48%) of the 21 patients with PSA < 1 ng/ml, obtained a pathological PET result. When the PSAdt was below six months, 86.7% of the patients obtained an abnormal PET. In the multivariate analysis, only Gleason’s scale was associated independently with an abnormal PET result. Conclusions: 68Ga-PSMA-11 PET shows a high disease detection rate in patients where other techniques showed negative or doubtful images. Almost 50% of patients with prostate cancer biochemical recurrence and low PSA levels (<1 ng/ml) have active disease on 68Ga-PSMA-11 PET, precisely where other radiotracers lack sensitivity.
关键词： Prostate-specific membrane antigen,68Ga-PSMA-11,Prostate cancer,Positron emission tomography
更新于2025-09-09 09:28:46
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Comparison of [68Ga]Ga-PSMA-HBED-CC PET versus Whole-Body Bone Scintigraphy for the Detection of Bone Metastases in Patients with Prostate Cancer
摘要： Aim: To compare [68Ga]Ga-PSMA-HBED-CC PET and (99m)Tc-DPD bone scintigraphy for the detection of bone metastases from prostate cancer. Methods: [68Ga]Ga-PSMA-HBED-CC PET/CT and (99m)Tc-DPD bone scintigraphy in 19 men with histopathological proven prostate cancer were compared to each other for the sensitivity/specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) for the detection of bone metastases. Results: According to the standard of reference lesion-based analysis of [68Ga]Ga-PSMA-HBED-CC PET and (99m)Tc-DPD bone scintigraphy reached a sensitivity of 45.6%/34%, specificity of 86.4%/81.4%, accuracy of 60.5%/51.2%, positive predictive value of 85.5%/76.1%, and negative predictive value of 47.7%/41.4%, respectively. Conclusion: [68Ga]Ga-PSMA-HBED-CC PET could detect significantly more bone metastases in prostate cancer than (99m)Tc-DPD bone scintigraphy.
关键词： Bone metastases,Prostate cancer,(99m)Tc-DPD scintigraphy,[68Ga]Ga HBED-CC PSMA,Detection rate
更新于2025-09-09 09:28:46
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Computer-Aided Diagnosis of Prostate Cancer on Diffusion Weighted Imaging: A Technical Review
摘要： Worldwide, prostate cancer is one of the most diagnosed cancer of males. However, developing efficient diagnostic techniques for prostate cancer is very essential and has a great clinical impact. These techniques can enhance the benefits from treatment and improve the chance of patients’ survival. Although, Transrectal Ultrasound (TRUS) guided biopsy is still the standard approach for prostate cancer diagnosing, it is not preferred due to its invasiveness. Therefore, there is a necessity to explore non-invasive methods that can detect the prostate cancer early. Several magnetic resonance imaging (MRI), e.g. T2 MRI, dynamic contrast-enhanced (DCE)- MRI, and diffusion weighted imaging (DWI), have been vastly utilized for prostate cancer detection. The main goal of this paper is to provide an overview of latest non-invasive Computer Aided Diagnosis (CAD) systems for diagnosing their prostate using DWI, highlighting experiments, implementation, and reported results. Moreover, the paper outlines the challenges of present diagnostic systems, and presents the current trends in solving these challenges.
关键词： DWI,Prostate cancer,CAD
更新于2025-09-09 09:28:46