Novel clinical risk calculator for improving cancer predictability of mpMRI fusion biopsy in prostates.
MRI-fusion biopsy
Prostate cancer
Risk calculator
Journal
International urology and nephrology
ISSN: 1573-2584
Titre abrégé: Int Urol Nephrol
Pays: Netherlands
ID NLM: 0262521
Informations de publication
Date de publication:
05 Apr 2024
05 Apr 2024
Historique:
received:
18
01
2024
accepted:
21
03
2024
medline:
5
4
2024
pubmed:
5
4
2024
entrez:
5
4
2024
Statut:
aheadofprint
Résumé
Prostate Imaging-Reporting and Data System (PI-RADS) assists in evaluating lesions on multiparametric magnetic resonance imaging (mpMRI), but there are still ongoing efforts in improving the predictive value for the presence of clinically significant PCa (csPCa) with a Gleason grade group ≥ 2 on Fusion-Biopsy. This pilot study intends to propose an easily implementable method for augmenting predictability of csPCa for PI-RADS. A cohort of 151 consecutive patients underwent mpMRI Fusion and random US Biopsy as a result of having at least one PI-RADS lesion grade 3-5 between January 1, 2019 and December 31, 2022. A single radiologist reads all films in this study applying PI-RADS V2. Of the 151 consecutive patients, 49 had a highest lesion of PI-RADS 3, 82 had a highest lesion of PI-RADS 4, and 20 had a highest lesion of PI-RADS 5. For each respective group, 12, 42, and 18 patients had proven csPCa. Two predictive models for csPCa were created by employing a logistical regression with parameters readily available to providers. The models had an AUC of 0.8133 and 0.8206, indicating promising effective models. PI-RADS classification has relevant predictability problems for grades 3 and 4. By applying the presented risk calculators, patients with PI-RADS 3 and 4 are better stratified, and thus, a significant number of patients can be spared biopsies with potential complications, such as infection and bleeding. The presented predictive models may be a valuable diagnostic tool, adding additional information in the clinical decision-making process for biopsies.
Identifiants
pubmed: 38578393
doi: 10.1007/s11255-024-04037-1
pii: 10.1007/s11255-024-04037-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Nature B.V.
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