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Diagnostics
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Recent Advances in Prostate Cancer Imaging and Biopsy Techniques
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Recent Advances in Prostate Cancer Imaging and Biopsy Techniques

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1064

Special Issue Editor

Dr. Abhinav Sidana

E-Mail Website
Guest Editor
Section of Urology, The University of Chicago, Chicago, IL, USA
Interests: kidney cancer; minimally invasive & robotic urologic surgery; prostate cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

There have been remarkable advances in the field of prostate imaging over the last few years, with prostate MRI and PSMA PET being more routinely used in clinical practice for the detection and staging of prostate cancer. In addition, prostate sampling techniques and approaches have evolved significantly, allowing for more accurate sampling of the prostate gland. This Special Issue will collate the latest updates on imaging and biopsy for prostate cancer diagnostics. Potential topics of interest include, but are not limited to, the following:

  • Multi-parametric MRI (mpMRI) of prostate;
  • Artificial intelligence and prostate MRI;
  • PSMA PET in detection and staging of prostate cancer;
  • Novel molecular tracers for prostate cancer imaging;
  • Magnetic resonance imaging (MRI)–transrectal ultrasound (TRUS) fusion prostate biopsy;
  • Transperineal prostate biopsy;
  • Future directions regarding prebiopsy imaging.

We are seeking high-quality original research and review articles to include in the collection. Following the initial triage stage, suitable manuscripts submitted to this Special Issue will undergo external peer review.

Dr. Abhinav Sidana
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. Diagnostics is an international peer-reviewed open access semimonthly 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 2600 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

  • multi-parametric MRI (mpMRI) of prostate
  • artificial intelligence and prostate MRI
  • PSMA PET in detection and staging of prostate cancer
  • novel molecular tracers for prostate cancer imaging
  • magnetic resonance imaging (MRI)–transrectal ultrasound (TRUS) fusion prostate biopsy
  • transperineal prostate biopsy
  • future directions regarding prebiopsy imaging

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

Published Papers (3 papers)

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Research

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10 pages, 1611 KiB  
Article
Prostate Cancer Diagnosis and Treatment in Elderly Patients: A Cross-Sectional Survey Exploring Practice Patterns and Preferences of Uro-Oncologists in Northeast Italy
by Filippo Carletti, Giuseppe Reitano, Laura Evangelista, Filippo Alongi, Alessandro Antonelli, Umberto Basso, Roberto Bortolus, Matteo Brunelli, Orazio Caffo, Fabrizio Dal Moro, Rocco De Vivo, Mario Gardi, Rossano Girometti, Andrea Guttilla, Fabio Matrone, Matteo Salgarello, Marco Andrea Signor, Fabio Zattoni, Gianluca Giannarini and on behalf of Gruppo Uro-Oncologico del Nord Est (GUONE)
Diagnostics 2025, 15(9), 1100; https://doi.org/10.3390/diagnostics15091100 - 25 Apr 2025
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Abstract
Background: The optimal diagnostic and therapeutic strategies for prostate cancer (PCa) in patients aged ≥75 years (mild-old and oldest-old) are still contentious. Resource allocation and ideal treatment for older patients are challenges, mainly due to their comorbidities and reduced life expectancy. This [...] Read more.
Background: The optimal diagnostic and therapeutic strategies for prostate cancer (PCa) in patients aged ≥75 years (mild-old and oldest-old) are still contentious. Resource allocation and ideal treatment for older patients are challenges, mainly due to their comorbidities and reduced life expectancy. This survey aims to assess current clinical practices and the experiences of healthcare providers in the diagnosis and management of elderly patients with PCa. Materials and Methods: In Northeast Italy, members of the Gruppo Uro-Oncologico del Nord-Est (GUONE) conducted a survey involving 104 physicians of different specialties (Nuclear Medicine, Medical Oncology, Radiation Oncology, Radiology, Urology) between 1 November 2024 and 30 November 2024. The survey encompassed 51 questions, evaluating various diagnostic and therapeutic scenarios. Results: Digital rectal exam (DRE) was recommended by 35.9% of physicians for patients aged 75 or older at risk of PCa. PSA testing was continued in 76.3% of these patients. For 36.5% of the physicians, there should be no age limit for prostate biopsy. Moreover, 42.6% of physicians recommended a magnetic resonance imaging (MRI)-guided prostate biopsy regardless of age. A prostate biopsy was deemed mandatory before initiating any form of hormonal therapy by 57.7% of the participants. For 22.3% and 34.7% of physicians, there should be no age limit for prostate MRI and PET/CT for staging purposes. Interestingly, PET/CT was not recommended in 52% of cases as a staging tool for patients older than 85 years. For patients without comorbidities, the age limit to consider radical prostatectomy (RP) was 75, with 58.6% of physicians in favor. There were no definitive limits for radiotherapy (RT). Chemotherapy had an age limit for 81.6% of the respondents; for 18.4%, 22.5%, and 26.5% of physicians, age limits were 75, 80, and 85 years, respectively. The use of androgen receptor pathway inhibitors (ARPIs) had no definitive age limits for 46.5% of respondents. For patients with no comorbidities and low-volume metastatic PCa, the preferred option was androgen deprivation therapy + ARPIs + RT. The follow-up schedule after RP or RT exhibited heterogeneity with no consensus regarding the frequency of PSA testing or the age at which it should be discontinued. Conclusions: This survey highlights the need for consensus guidelines in diagnosing and managing mild-old and oldest-old elderly PCa patients. With the aging population, standardized protocols are essential to ensure optimal care. Full article
(This article belongs to the Special Issue Recent Advances in Prostate Cancer Imaging and Biopsy Techniques)
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Review

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30 pages, 7513 KiB  
Review
A Narrative Review of Artificial Intelligence in MRI-Guided Prostate Cancer Diagnosis: Addressing Key Challenges
by Deniz Alis, Aslihan Onay, Evrim Colak, Ercan Karaarslan and Baris Bakir
Diagnostics 2025, 15(11), 1342; https://doi.org/10.3390/diagnostics15111342 - 26 May 2025
Abstract
Background/Objectives: Magnetic resonance imaging (MRI) is crucial in detecting suspicious lesions and diagnosing clinically significant prostate cancer (csPCa). However, variability in MRI-targeted diagnostic pathways arises due to factors such as patient characteristics, imaging protocols, and radiologist expertise. Artificial intelligence (AI) offers potential [...] Read more.
Background/Objectives: Magnetic resonance imaging (MRI) is crucial in detecting suspicious lesions and diagnosing clinically significant prostate cancer (csPCa). However, variability in MRI-targeted diagnostic pathways arises due to factors such as patient characteristics, imaging protocols, and radiologist expertise. Artificial intelligence (AI) offers potential solutions to these challenges by enhancing diagnostic accuracy and efficiency. Methods: This narrative review explores AI techniques, particularly machine learning and deep learning, in the context of prostate cancer diagnosis. It examines their application in improving MRI scan quality, detecting artifacts, and assisting radiologists in lesion detection and interpretation. It also considers how AI helps to reduce reading time and inter-reader variability. Results: AI has demonstrated sensitivity that is generally comparable to experienced radiologists, although specificity tends to be lower, potentially increasing false-positive rates. The clinical impact of these results requires validation in larger, prospective multicenter studies. AI is effective in identifying artifacts, assessing MRI quality, and assisting in diagnostic efficiency by providing second opinions and automating lesion detection. However, variability in study methodologies, datasets, and imaging protocols can impact AI’s generalizability, limiting its broader clinical application. Conclusions: While AI shows significant promise in enhancing diagnostic accuracy and efficiency for csPCa detection, challenges remain, particularly with the generalizability of AI models. To improve AI robustness and integration into clinical practice, multicenter datasets and transparent reporting are essential. Further development, validation, and standardization are required for AI’s widespread clinical adoption. Full article
(This article belongs to the Special Issue Recent Advances in Prostate Cancer Imaging and Biopsy Techniques)
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17 pages, 2465 KiB  
Review
Post-Treatment Imaging in Focal Therapy: Understanding TARGET and PI-FAB Scoring Systems
by Haidy Megahed, Samuel Tremblay, Jason Koehler, Simon Han, Ahmed Hamimi, Aytekin Oto and Abhinav Sidana
Diagnostics 2025, 15(11), 1328; https://doi.org/10.3390/diagnostics15111328 - 26 May 2025
Viewed by 165
Abstract
As the adoption of focal therapy (FT) for prostate cancer (PCa) grows, the demand for accurate post-treatment imaging to monitor outcomes and detect residual or recurrent cancer increases. Traditional diagnostic systems like the Prostate Imaging Reporting and Data System (PI-RADS) are ill-suited for [...] Read more.
As the adoption of focal therapy (FT) for prostate cancer (PCa) grows, the demand for accurate post-treatment imaging to monitor outcomes and detect residual or recurrent cancer increases. Traditional diagnostic systems like the Prostate Imaging Reporting and Data System (PI-RADS) are ill-suited for post-FT evaluations due to treatment-induced tissue changes. MRI-based scoring systems specific for evaluation after FT have been developed to address these challenges and improve post-FT imaging accuracy by distinguishing benign alterations from recurrence. The currently developed scoring systems are Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) and Prostate Imaging after Focal Ablation (PI-FAB). In this review, we describe and compare these two systems. These scoring systems standardize imaging assessments, enhance follow-up care, and support clinical decision-making. While promising, TARGET and PI-FAB require further large-scale validation to confirm their utility. Nevertheless, they represent critical advances in optimizing PCa management, particularly for patients undergoing FT, by improving diagnostic accuracy and guiding treatment decisions. Full article
(This article belongs to the Special Issue Recent Advances in Prostate Cancer Imaging and Biopsy Techniques)
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