T-staging of prostate cancer: Identification of useful signs to standardize detection of posterolateral extraprostatic extension on prostate MRI.

Clin Imaging

Department of Radiology and Nuclear Medicine, Ghent University Hospital, Ghent, Corneel Heymanslaan 10, 9000 Gent, Belgium. Electronic address:

Published: January 2020

Objectives: To determine the prevalence and predictive value of a series of commonly used MRI criteria for posterolateral extraprostatic extension (EPE) of prostate cancer (PCa).

Methods: The presence of EPE in index lesions visible on prebiopsy mpMRI (T2w, DWI and DCE on a 3 Tesla-system) of biopsy-proven PCa patients was blindly assessed retrospectively by two radiologists with 8- and 17-years of experience on the basis of 8 commonly used staging criteria. Radical prostatectomy was used as standard of reference. The prevalences and positive predictive values (PPV) of all criteria were calculated for each reader separately and averaged for the two readers together. Cohen's K and percentage of agreement were used to assess the interobserver agreement.

Results: In 51 patients (mean age: 63 years; mean PSA: 17.2 ng/ml), tumor-capsule contact was the most prevalent sign (average 56,9%), but with the lowest PPV (average 51.9%), although increasing with broader capsular contact (56.5% if ≥10 mm; 87.5% if ≥20 mm; 100% if ≥25 mm). "Early signs" of EPE such as bulging, capsular disruption and unsharp prostatic margin showed a prevalence of 11.8%-18.6% on average, with 74.5%-86.3% of agreement; the average PPV range was 69.0%-75.0%. "Late signs" of EPE such as irregular prostatic contour, periprostatic fat infiltration, rectoprostatic angle obliteration and periprostatic mass showed a prevalence of 2.9%-8.8% on average, with 86.3%-94.1% of agreement; the average PPVs ranged between 85.7% and 100%.

Conclusions: "Early" signs of EPE show high prevalences but low PPVs, while "late" signs show lower prevalences but higher PPVs. MRI-staging following this chronological concept can standardize morphologic staging and decrease the existing multi-reader variability.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.clinimag.2019.08.007DOI Listing

Publication Analysis

Top Keywords

prostate cancer
8
posterolateral extraprostatic
8
extraprostatic extension
8
signs" epe
8
agreement average
8
average
6
epe
5
t-staging prostate
4
cancer identification
4
identification signs
4

Similar Publications

The cascade of events leading to tumor formation includes induction of a tumor supporting neovasculature, as a primary hallmark of cancer. Developing vasculature is difficult to evaluate but can be captured using microfluidic chip technology and patient derived cells. Herein, we established an approach to investigate the mechanisms promoting tumor vascularization and vascular targeted therapies via co-culture of cancer spheroids and endothelial cells in a three dimensional environment.

View Article and Find Full Text PDF

Adaptive Treatment of Metastatic Prostate Cancer Using Generative Artificial Intelligence.

Clin Med Insights Oncol

January 2025

Ted Rogers School of Information Technology Management, Toronto Metropolitan University, Toronto, ON, Canada.

Despite the expanding therapeutic options available to cancer patients, therapeutic resistance, disease recurrence, and metastasis persist as hallmark challenges in the treatment of cancer. The rise to prominence of generative artificial intelligence (GenAI) in many realms of human activities is compelling the consideration of its capabilities as a potential lever to advance the development of effective cancer treatments. This article presents a hypothetical case study on the application of generative pre-trained transformers (GPTs) to the treatment of metastatic prostate cancer (mPC).

View Article and Find Full Text PDF

Ultrasound radiomics model based on grayscale transrectal ultrasound-guided biopsy for diagnosing prostate cancer and predicting distant metastasis.

Int Urol Nephrol

January 2025

Department of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.

Objective: A prostate ultrasound (US) imaging omics model was established to assess its effectiveness in diagnosing prostate cancer (PCa), predicting Gleason score (GS), and determining the likelihood of distant metastasis.

Methods: US images of patients with prostate pathology confirmed by biopsy or surgery at our hospital were retrospectively analyzed. Regions of interest (ROI) segmentation, feature extraction, feature screening, and the construction and training of the radiomics model were performed.

View Article and Find Full Text PDF

Prostate cancer (PCa) is the second leading cause of cancer-related mortality among men in the United States. While PCa initially responds to androgen deprivation therapy, a significant portion progresses to castration-resistant PCa. Approximately 20-25% of these cases acquire aggressive neuroendocrine (NE) features, ultimately leading to neuroendocrine prostate cancer (NEPC).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!