Evaluating diagnostic accuracy of the Prostate Imaging after Focal Ablation (PI-FAB) scoring system in detecting clinically significant prostate cancer after primary focal therapy.

Authors

David Gelikman

David G Gelikman

Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD

David G Gelikman , Alexander P Kenigsberg , Enis C Yilmaz , Sahil H Parikh , Jason Hyman , Hannah Huth , Christopher R Koller , Daniel Nethala , Charles Hesswani , Sandeep Gurram , Peter L Choyke , Brad Wood , Peter A Pinto , Baris Turkbey

Organizations

Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, Center for Interventional Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD

Research Funding

No funding sources reported

Background: Focal therapy (FT) has emerged as a promising, organ-sparing alternative to radiotherapy and radical prostatectomy for the management of localized prostate cancer (PCa). Multi-parametric magnetic resonance imaging (mpMRI) is often used to monitor for post-FT tumor recurrence. However, post-treatment mpMRI assessment can be quite challenging due to treatment-related changes and distortion of the prostate gland anatomy. The Prostate Imaging after Focal Ablation (PI-FAB) score was proposed by Giganti et al. in May 2023 as a standardized three-point scale for rating mpMRI sequences to aid in decision for follow-up imaging or biopsy. The purpose of this study is to investigate the performance of this new scoring system in predicting recurrent clinically significant prostate cancer (csPCa), defined as Gleason grade > 1 disease. Methods: Patients with localized PCa who underwent focal laser ablation (FLA), high-intensity focused ultrasound (HIFU), or cryoablation who had post-treatment mpMRI imaging and prostate biopsy were included in the study. The mpMRIs were evaluated and assigned a PI-FAB score (range, 1-3) by one genitourinary radiologist with 16 years of experience in PCa imaging. A total of 39 patients were included in the study, of which 30 patients underwent FLA, 6 patients underwent HIFU, and 3 patients underwent cryoablation. PI-FAB scores were correlated with MRI/TRUS fusion-guided and systematic prostate biopsies. A confusion matrix was constructed using confirmed csPCa predicted by PI-FAB scores of 3. Key performance metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated to assess the diagnostic accuracy of the PI-FAB score. Results: Among the 39 patients included in this study, the distribution of PI-FAB scores was as follows: 16 (41.0%) scored as PI-FAB 1, 1 (2.6%) as PI-FAB 2, and 22 (56.4%) as PI-FAB 3. Eighteen (46.2%) patients had pathologically confirmed csPCa. An additional 5 patients had Gleason grade group 1 disease, bringing the total number of PCa cases to 23 (59%). Utilizing a cutoff score of PI-FAB 3 for the identification of csPCa yielded a sensitivity of 77.8% (14/18), specificity of 61.9% (13/21), PPV of 63.6% (14/22), NPV of 76.5% (13/17), and accuracy of 69.2% (27/39). The PI-FAB scoring system missed four cases of csPCa in our cohort, equating to a false negative rate of 22.2% (4/18). Conclusions: The new PI-FAB scoring system demonstrates potential as a standardized evaluation of mpMRI. Its moderately high sensitivity can be useful for stratifying patients who may benefit from subsequent prostate biopsy, but PI-FAB should be further validated in larger cohorts to better understand its utility and potential.

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Abstract Details

Meeting

2024 ASCO Genitourinary Cancers Symposium

Session Type

Poster Session

Session Title

Poster Session A: Prostate Cancer

Track

Prostate Cancer - Advanced,Prostate Cancer - Localized

Sub Track

Diagnostics and Imaging

Citation

J Clin Oncol 42, 2024 (suppl 4; abstr 277)

DOI

10.1200/JCO.2024.42.4_suppl.277

Abstract #

277

Poster Bd #

L12

Abstract Disclosures

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