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Prostate volume prediction on MRI: tools, accuracy and variability

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A Correction to this article was published on 23 March 2022

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Abstract

Objective

A reliable estimation of prostate volume (PV) is essential to prostate cancer management. The objective of our multi-rater study was to compare intra- and inter-rater variability of PV from manual planimetry and ellipsoid formulas.

Methods

Forty treatment-naive patients who underwent prostate MRI were selected from a local database. PV and corresponding PSA density (PSAd) were estimated on 3D T2-weighted MRI (3 T) by 7 independent radiologists using the traditional ellipsoid formula (TEF), the newer biproximate ellipsoid formula (BPEF), and the manual planimetry method (MPM) used as ground truth. Intra- and inter-rater variability was calculated using the mixed model–based intraclass correlation coefficient (ICC).

Results

Mean volumes were 67.00 (± 36.61), 66.07 (± 35.03), and 64.77 (± 38.27) cm3 with the TEF, BPEF, and MPM methods, respectively. Both TEF and BPEF overestimated PV relative to MPM, with the former presenting significant differences (+ 1.91 cm3, IQ = [− 0.33 cm3, 5.07 cm3], p val = 0.03). Both intra- (ICC > 0.90) and inter-rater (ICC > 0.90) reproducibility were excellent. MPM had the highest inter-rater reproducibility (ICC = 0.999). Inter-rater PV variation led to discrepancies in classification according to the clinical criterion of PSAd > 0.15 ng/mL for 2 patients (5%), 7 patients (17.5%), and 9 patients (22.5%) when using MPM, TEF, and BPEF, respectively.

Conclusion

PV measurements using ellipsoid formulas and MPM are highly reproducible. MPM is a robust method for PV assessment and PSAd calculation, with the lowest variability. TEF showed a high degree of concordance with MPM but a slight overestimation of PV. Precise anatomic landmarks as defined with the BPEF led to a more accurate PV estimation, but also to a higher variability.

Key Points

• Manual planimetry used for prostate volume estimation is robust and reproducible, with the lowest variability between readers.

• Ellipsoid formulas are accurate and reproducible but with higher variability between readers.

• The traditional ellipsoid formula tends to overestimate prostate volume.

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Abbreviations

AP:

Antero-posterior

BPEF:

Biproximate ellipsoid formula

CsPCa:

Clinically significant prostate cancer

DRE:

Digital rectal exam

ICC:

Intraclass correlation coefficient

IQ:

Interquartile

MPM:

Manual planimetry measurement

PCa:

Prostate cancer

PSA:

Prostate-specific antigen

PSAd:

Prostate-specific antigen density (mpmPSAd, tefPSAd, and bpefPSAd are PSAd obtained using a volume estimated, respectively, by MPM, TEF, and BPEF methods)

PV:

Prostate volume

rSTD:

Relative standard deviation

T:

Tesla

T2W:

T2-weighted

TEF:

Traditional ellipsoid formula

TRUS:

Transrectal ultrasound

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Acknowledgements

We thank Julien Castelneau, software engineer of Inria, for his help in the development of MedInria Software (MedInria—medical image visualization and processing software by Inria https://med.inria.fr-RRID:SCR_001462). This work has been supported by the French government, through the 3IA Côte d’Azur Investments in the Future project managed by the National Research Agency (ANR) with the reference numbers ANR-19-P3IA-0002 and ANR-17-EURE-0004. Data were extracted from the Clinical Data Warehouse of the Greater Paris University Hospitals (Assistance Publique – Hôpitaux de Paris). The authors are grateful to the members of the AP-HP WIND and URC teams, and in particular Cyrina Saussol and Aurélien Maire.

We also thank Dr. Hari Sreedhar for a thorough proofreading of this paper.

Funding

The authors state that this work has not received any funding.

Author information

Author notes

  1. Dimitri Hamzaoui and Sarah Montagne contributed equally to this work.

Authors and Affiliations

  1. Inria, Epione Team, Sophia Antipolis, Université Côte d’Azur, Nice, France

    Dimitri Hamzaoui, Nicholas Ayache & Hervé Delingette

  2. Academic Department of Radiology, Hôpital Pitié-Salpétrière, Assistance Publique des Hôpitaux de Paris, 47 bd de l’Hôpital, 75013, Paris, France

    Sarah Montagne, Alexandre Allera, Malek Ezziane, Anna Luzurier, Raphaëlle Quint, Mehdi Kalai & Raphaële Renard-Penna

  3. Academic Department of Radiology, Hôpital Tenon, Assistance Publique des Hôpitaux de Paris, Paris, France

    Sarah Montagne & Raphaële Renard-Penna

  4. GRC n° 5, Oncotype-Uro, Sorbonne Universités, Paris, France

    Sarah Montagne & Raphaële Renard-Penna

  5. Department of Public Health, Pitié-Salpétrière Academic Hospital, AP-HP, Sorbonne Universités, AP-HP, CIC-P 1421, Paris, France

    Benjamin Granger

  6. INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique, UMR 1136, CIC-1421, Hôpital Pitié-Salpétrière, AP-HP, Sorbonne Université, Paris, France

    Benjamin Granger

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Corresponding author

Correspondence to Sarah Montagne.

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Guarantor

The scientific guarantor of this publication is Pr Raphaële Renard-Penna.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Dr. Benjamin Granger kindly provided statistical advice for this manuscript. Also, one of the authors, Dimitri Hamzaoui, has significant statistical expertise.

Informed consent

According to French regulation, consent was waived as the MRI were acquired as part of the routine clinical care of the patients and the design of our study was retrospective.

Ethical approval

The data were made available by the data warehouse of the AP-HP, and the study was approved by the Ethical and Scientific Board of the AP-HP (IRB00011591).

Methodology

• retrospective

• observational

• performed in 2 institutions

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The original online version of this article was revised: the name of the author Raphaële Renard-Penna was incorrectly given as Raphaële Renard Penna. The name was also tagged incorrectly in the HTML version of this article. The author's first name is Raphaële and the family name is Renard-Penna.

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Hamzaoui, D., Montagne, S., Granger, B. et al. Prostate volume prediction on MRI: tools, accuracy and variability. Eur Radiol 32, 4931–4941 (2022). https://doi.org/10.1007/s00330-022-08554-4

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