Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.3
2.8
Journals
Current Oncology
Special Issues
New Aspects in Prostate Cancer Imaging
share announcement

New Aspects in Prostate Cancer Imaging

A special issue of Current Oncology (ISSN 1718-7729). This special issue belongs to the section "Genitourinary Oncology".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 3566

Special Issue Editor

Dr. Bernhard Grubmüller

E-Mail Website
Guest Editor
Department of Urology, University Hospital Krems, Karl Landsteiner University of Health Sciences, 3500 Krems, Austria
Interests: uro-oncology; prostate cancer; molecular imaging

Special Issue Information

Dear Colleagues,

The usage and field of imaging in prostate cancer (PC) has developed tremendously over the last years, including significant advancements revolutionizing its detection, diagnosis and management. PC is one of the most prevalent malignancies affecting men worldwide; therefore, accurate imaging plays a crucial role in early detection and treatment planning.

Traditional imaging modalities, such as transrectal ultrasound and CT scans, have been limited in their ability to provide precise information about tumor location, size and aggressiveness. However, the advent of multiparametric magnetic resonance imaging (mpMRI) has emerged as a game-changer in PC diagnostics. mpMRI combines various sequences to visualize the prostate gland and surrounding tissues in unprecedented detail, enabling radiologists to identify suspicious lesions and guide targeted biopsies more accurately.

Additionally, the integration of positron emission tomography (PET) with novel radiotracers, such as prostate-specific membrane antigen (PSMA), has significantly improved PC primary staging and restaging. PSMA–PET offers unique sensitivity in detecting PC cells, even at low concentrations, helping clinicians assess disease spread and identify potential sites of metastases.

Furthermore, advancements in artificial intelligence and machine learning have facilitated the development of sophisticated image analysis algorithms, aiding in the automated interpretation of imaging data and providing clinicians with valuable insights for personalized treatment planning.

To summarize, the last decade has witnessed remarkable progress in PC imaging, with the introduction of mpMRI, PSMA–PET and AI-based analyses. These innovations have elevated the standard of care, enabling earlier detection, more accurate diagnosis and improved management of PC patients. As technology continues to evolve, the future holds great promise for further enhancing the efficacy of PC imaging and ultimately improving patient outcomes.

Original research articles and reviews are welcome for submission to this Special Issue. We look forward to receiving your contributions.

Dr. Bernhard Grubmüller
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Current Oncology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • prostate cancer imaging
  • multiparametric magnetic resonance imaging
  • positron emission tomography
  • prostate specific membrane antigen
  • cancer detection
  • novel radiotracers
  • artificial intelligence
  • machine learning

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

10 pages, 2301 KiB  
Article
Clinically Significant Prostate Cancer Prediction Using Multimodal Deep Learning with Prostate-Specific Antigen Restriction
by Hayato Takeda, Jun Akatsuka, Tomonari Kiriyama, Yuka Toyama, Yasushi Numata, Hiromu Morikawa, Kotaro Tsutsumi, Mami Takadate, Hiroya Hasegawa, Hikaru Mikami, Kotaro Obayashi, Yuki Endo, Takayuki Takahashi, Manabu Fukumoto, Ryuji Ohashi, Akira Shimizu, Go Kimura, Yukihiro Kondo and Yoichiro Yamamoto
Curr. Oncol. 2024, 31(11), 7180-7189; https://doi.org/10.3390/curroncol31110530 - 15 Nov 2024
Viewed by 397
Abstract
Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low–intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accuracy of deep learning analysis using multimodal medical data focused on clinically significant PCa [...] Read more.
Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low–intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accuracy of deep learning analysis using multimodal medical data focused on clinically significant PCa in patients with PSA ≤ 20 ng/mL. Our cohort study included 178 consecutive patients who underwent ultrasound-guided prostate biopsy. Deep learning analyses were applied to predict clinically significant PCa. We generated receiver operating characteristic curves and calculated the corresponding area under the curve (AUC) to assess the prediction. The AUC of the integrated medical data using our multimodal deep learning approach was 0.878 (95% confidence interval [CI]: 0.772–0.984) in all patients without PSA restriction. Despite the reduced predictive ability of PSA when restricted to PSA ≤ 20 ng/mL (n = 122), the AUC was 0.862 (95% CI: 0.723–1.000), complemented by imaging data. In addition, we assessed clinical presentations and images belonging to representative false-negative and false-positive cases. Our multimodal deep learning approach assists physicians in determining treatment strategies by predicting clinically significant PCa in patients with PSA ≤ 20 ng/mL before biopsy, contributing to personalized medical workflows for PCa management. Full article
(This article belongs to the Special Issue New Aspects in Prostate Cancer Imaging)
►▼ Show Figures

Figure 1

Review

Jump to: Research

24 pages, 1743 KiB  
Review
Role of Systematic Biopsy in the Era of Targeted Biopsy: A Review
by Wojciech Malewski, Tomasz Milecki, Omar Tayara, Sławomir Poletajew, Piotr Kryst, Andrzej Tokarczyk and Łukasz Nyk
Curr. Oncol. 2024, 31(9), 5171-5194; https://doi.org/10.3390/curroncol31090383 - 3 Sep 2024
Viewed by 1325
Abstract
Prostate cancer (PCa) is a major public health issue, as the second most common cancer and the fifth leading cause of cancer-related deaths among men. Many PCa cases are indolent and pose minimal risk, making active surveillance a suitable management approach. However, clinically [...] Read more.
Prostate cancer (PCa) is a major public health issue, as the second most common cancer and the fifth leading cause of cancer-related deaths among men. Many PCa cases are indolent and pose minimal risk, making active surveillance a suitable management approach. However, clinically significant prostate carcinoma (csPCa) can lead to serious health issues, including progression, metastasis, and death. Differentiating between insignificant prostate cancer (inPCa) and csPCa is crucial for determining appropriate treatment. Diagnosis of PCa primarily involves trans-perineal and transrectal systematic biopsies. Systematic transrectal prostate biopsy, which typically collects 10–12 tissue samples, is a standard method, but it can miss csPCa and is associated with some complications. Recent advancements, such as magnetic resonance imaging (MRI)-targeted biopsies, have been suggested to improve risk stratification and reduce overtreatment of inPCa and undertreatment of csPCa, thereby enhancing patient quality of life and treatment outcomes. Guided biopsies are increasingly recommended for their ability to better detect high-risk cancers while reducing identification of low-risk cases. MRI-targeted biopsies, especially when used as an initial biopsy in biopsy-naïve patients and those under active surveillance, have become more common. Utilization of MRI-TB alone can decrease septic complications; however, the combining of targeted biopsies with perilesional sampling is recommended for optimal detection of csPCa. Future advancements in imaging and biopsy techniques, including AI-augmented lesion detection and robotic-assisted sampling, promise to further improve the accuracy and effectiveness of PCa detection. Full article
(This article belongs to the Special Issue New Aspects in Prostate Cancer Imaging)
►▼ Show Figures

Figure 1

13 pages, 1383 KiB  
Review
Prostate-Specific Membrane Antigen Expression in Patients with Primary Prostate Cancer: Diagnostic and Prognostic Value in Positron Emission Tomography-Prostate-Specific Membrane Antigen
by Omar Tayara, Sławomir Poletajew, Wojciech Malewski, Jolanta Kunikowska, Kacper Pełka, Piotr Kryst and Łukasz Nyk
Curr. Oncol. 2024, 31(8), 4165-4177; https://doi.org/10.3390/curroncol31080311 - 24 Jul 2024
Viewed by 1242
Abstract
Prostate cancer represents a significant public health challenge, with its management requiring precise diagnostic and prognostic tools. Prostate-specific membrane antigen (PSMA), a cell surface enzyme overexpressed in prostate cancer cells, has emerged as a pivotal biomarker. PSMA’s ability to increase the sensitivity of [...] Read more.
Prostate cancer represents a significant public health challenge, with its management requiring precise diagnostic and prognostic tools. Prostate-specific membrane antigen (PSMA), a cell surface enzyme overexpressed in prostate cancer cells, has emerged as a pivotal biomarker. PSMA’s ability to increase the sensitivity of PET imaging has revolutionized its application in the clinical management of prostate cancer. The advancements in PET-PSMA imaging technologies and methodologies, including the development of PSMA-targeted radiotracers and optimized imaging protocols, led to diagnostic accuracy and clinical utility across different stages of prostate cancer. This highlights its superiority in staging and its comparative effectiveness against conventional imaging modalities. This paper analyzes the impact of PET-PSMA on prostate cancer management, discussing the existing challenges and suggesting future research directions. The integration of recent studies and reviews underscores the evolving understanding of PET-PSMA imaging, marking its significant but still expanding role in clinical practice. This comprehensive review serves as a crucial resource for clinicians and researchers involved in the multifaceted domains of prostate cancer diagnosis, treatment, and management. Full article
(This article belongs to the Special Issue New Aspects in Prostate Cancer Imaging)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop