AI Article Synopsis
- Up to 50% of men with positive MRI findings for prostate cancer may not have significant cancer, prompting the need for better diagnostic methods like VERDICT MRI.
- A study involving 303 men showed that higher fractional intracellular volume (FIC) values in lesions were linked to clinically significant prostate cancer (csPCa), while apparent diffusion coefficient (ADC) values were lower for certain lesions with csPCa.
- The research indicated that FIC had better diagnostic performance for identifying csPCa than ADC, with an area under the curve (AUC) of 0.96 compared to ADC’s 0.85.
Article Abstract
Background In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert score of 3 or higher) have no clinically significant (Gleason score ≤3+3, benign) biopsy findings. Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor (VERDICT) MRI analysis could improve the stratification of positive mpMRI findings. Purpose To evaluate VERDICT MRI, mpMRI-derived apparent diffusion coefficient (ADC), and prostate-specific antigen density (PSAD) as determinants of clinically significant PCa (csPCa). Materials and Methods Between April 2016 and December 2019, men suspected of having PCa were prospectively recruited from two centers and underwent VERDICT MRI and mpMRI at one center before undergoing targeted biopsy. Biopsied lesion ADC, lesion-derived fractional intracellular volume (FIC), and PSAD were compared between men with csPCa and those without csPCa, using nonparametric tests subdivided by Likert scores. Area under the receiver operating characteristic curve (AUC) was calculated to test diagnostic performance. Results Among 303 biopsy-naive men, 165 study participants (mean age, 65 years ± 7 [SD]) underwent targeted biopsy; of these, 73 had csPCa. Median lesion FIC was higher in men with csPCa (FIC, 0.53) than in those without csPCa (FIC, 0.18) for Likert 3 ( = .002) and Likert 4 (0.60 vs 0.28, < .001) lesions. Median lesion ADC was lower for Likert 4 lesions with csPCa (0.86 × 10 mm/sec) compared with lesions without csPCa (1.12 × 10 mm/sec, = .03), but there was no evidence of a difference for Likert 3 lesions (0.97 × 10 mm/sec vs 1.20 × 10 mm/sec, = .09). PSAD also showed no difference for Likert 3 (0.17 ng/mL vs 0.12 ng/mL, = .07) or Likert 4 (0.14 ng/mL vs 0.12 ng/mL, = .47) lesions. The diagnostic performance of FIC (AUC, 0.96; 95% CI: 0.93, 1.00) was higher ( = .02) than that of ADC (AUC, 0.85; 95% CI: 0.79, 0.91) and PSAD (AUC, 0.74; 95% CI: 0.66, 0.82) for the presence of csPCa in biopsied lesions. Conclusion Lesion fractional intracellular volume enabled better classification of clinically significant prostate cancer than did apparent diffusion coefficient and prostate-specific antigen density. Clinical trial registration no. NCT02689271 © RSNA, 2022
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1148/radiol.212536 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Virtual reality: a game-changer in the diagnosis and surgical planning of astrocytoma grade III: a case report.
J Med Case Rep
August 2024
Neurosurgery Department, Military Medical Services Administration, Tishreen Military Hospital, Damascus, Syrian Arab Republic.
Background: In the dynamic realm of modern medicine, the advent of virtual reality technology heralds a transformative era, reshaping the contours of diagnosis and surgical planning with its immersive prowess. This study delves into the groundbreaking application of virtual reality in the intricate dance of neurosurgery, particularly spotlighting its role in the management of astrocytoma grade III-a cerebral challenge of significant complexity.
Case Presentation: A 30-year-old Middle Eastern man from Syria grappled with the invisible tendrils of pain, manifesting as persistent headaches and a numbing sensation that crept into his neck and extremities.
MRI-based virtual pathology of the prostate.
MAGMA
August 2024
Department of Radiodiagnosis, King George's Medical University, Lucknow, India.
Prostate cancer poses significant diagnostic challenges, with conventional methods like prostate-specific antigen (PSA) screening and transrectal ultrasound (TRUS)-guided biopsies often leading to overdiagnosis or miss clinically significant cancers. Multiparametric MRI (mpMRI) has emerged as a more reliable tool. However, it is limited by high inter-observer variability and radiologists missing up to 30% of clinically significant cancers.
View Article and Find Full Text PDFssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.
Magn Reson Med
November 2024
Center for Medical Image Computing, Department of Computer Science, University College London, London, UK.
Purpose: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.
Methods: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning.
Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology.
J Magn Reson Imaging
October 2024
Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed.
View Article and Find Full Text PDFManagement Strategy for Prostate Imaging Reporting and Data System Category 3 Lesions.
Curr Urol Rep
December 2023
Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China.
Purpose Of Review: Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions present a clinical dilemma due to their uncertain nature, which complicates the development of a definitive management strategy. These lesions have an incidence rate of approximately 22-32%, with clinically significant prostate cancer (csPCa) accounting for about 10-30%. Therefore, a thorough evaluation is warranted.
View Article and Find Full Text PDFWant 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!