The Role of mpMRI in the Assessment of Prostate Cancer Recurrence Using the PI-RR System: Diagnostic Accuracy and Interobserver Agreement in Readers with Different Expertise.

biochemical recurrence multiparametric MRI prostate cancer

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
20 Jan 2023
Historique:
received: 13 12 2022
revised: 09 01 2023
accepted: 17 01 2023
entrez: 11 2 2023
pubmed: 12 2 2023
medline: 12 2 2023
Statut: epublish

Résumé

treated prostate cancer (PCa) patients develop biochemical recurrence (BCR) in 27-53% of cases; the role of MRI in this setting is still controversial. In 2021 a panel of experts proposed a "Prostate Imaging-Recurrence Reporting" (PI-RR) score, aiming to standardize the reporting. The aim of our study is to evaluate the reproducibility of the PI-RR scoring system among readers with different expertise. in this monocentric, retrospective observational study, the images of patients who underwent MRI with BCR from January 2017 to January 2022 were analyzed by two radiologists and a radiology resident. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were obtained. Interobserver agreement was calculated. The percentage of the PI-RR score of 3 was estimated to find out the proportion of uncertain exams reported among the readers. a total of seventy-six patients were included in our study: eight previously treated with RT and sixty-eight who underwent surgery. The accuracy range was 75-80%, the sensitivity 68.4-71.1%, the specificity 81.6-89.5%, PPV 78.8-87.1%, and NPV 72.1-75.6%. The inter-reader agreement using a binary evaluation (PI-RR ≥ 3 as positive mpMRI) demonstrated a correlation coefficient (k) of 0.74 (95% CI: 0.62-0.87). The percentage for the PI-RR score of 3 was 6.6% for reader one, 14.5% for reader two, and 2.6% for reader three. this study confirmed the good accuracy of mpMRI in the detection of local recurrence of PCa and the good reproducibility of PI-RR score among all readers, confirming it to be a promising tool for the standardization of the assessment of patients with BCR.

Sections du résumé

BACKGROUND BACKGROUND
treated prostate cancer (PCa) patients develop biochemical recurrence (BCR) in 27-53% of cases; the role of MRI in this setting is still controversial. In 2021 a panel of experts proposed a "Prostate Imaging-Recurrence Reporting" (PI-RR) score, aiming to standardize the reporting. The aim of our study is to evaluate the reproducibility of the PI-RR scoring system among readers with different expertise.
METHODS METHODS
in this monocentric, retrospective observational study, the images of patients who underwent MRI with BCR from January 2017 to January 2022 were analyzed by two radiologists and a radiology resident. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were obtained. Interobserver agreement was calculated. The percentage of the PI-RR score of 3 was estimated to find out the proportion of uncertain exams reported among the readers.
RESULTS RESULTS
a total of seventy-six patients were included in our study: eight previously treated with RT and sixty-eight who underwent surgery. The accuracy range was 75-80%, the sensitivity 68.4-71.1%, the specificity 81.6-89.5%, PPV 78.8-87.1%, and NPV 72.1-75.6%. The inter-reader agreement using a binary evaluation (PI-RR ≥ 3 as positive mpMRI) demonstrated a correlation coefficient (k) of 0.74 (95% CI: 0.62-0.87). The percentage for the PI-RR score of 3 was 6.6% for reader one, 14.5% for reader two, and 2.6% for reader three.
CONCLUSION CONCLUSIONS
this study confirmed the good accuracy of mpMRI in the detection of local recurrence of PCa and the good reproducibility of PI-RR score among all readers, confirming it to be a promising tool for the standardization of the assessment of patients with BCR.

Identifiants

pubmed: 36766492
pii: diagnostics13030387
doi: 10.3390/diagnostics13030387
pmc: PMC9914595
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Ministero della Salute
ID : Grant for Current Research R779A

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Auteurs

Chiara Bergaglio (C)

Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy.

Veronica Giasotto (V)

Department of Radiology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Michela Marcenaro (M)

Department of Radiation Oncology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Salvina Barra (S)

Department of Radiation Oncology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Marianna Turazzi (M)

Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy.

Matteo Bauckneht (M)

Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy.
Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Alessandro Casaleggio (A)

Department of Radiology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Francesca Sciabà (F)

Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy.

Carlo Terrone (C)

Department of Urology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.
Department of Surgical Integrated Sciences (DISC), Urology Section, University of Genova, 16126 Genova, Italy.

Guglielmo Mantica (G)

Department of Urology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.
Department of Surgical Integrated Sciences (DISC), Urology Section, University of Genova, 16126 Genova, Italy.

Marco Borghesi (M)

Department of Urology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.
Department of Surgical Integrated Sciences (DISC), Urology Section, University of Genova, 16126 Genova, Italy.

Alessio Signori (A)

Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy.

Bruno Spina (B)

Pathology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Nataniele Piol (N)

Anatomia Patologica Universitaria Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Elisa Zanardi (E)

Academic Unit of Medical Oncology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Giuseppe Fornarini (G)

Medical Oncology Unit 1, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Jeries Paolo Zawaideh (JP)

Department of Radiology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.

Classifications MeSH