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A new computer-aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: results of a multicentre validation study

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Abstract

Objectives

To prospectively assess an innovative computer-aided diagnostic technology that quantifies characteristic features of backscattered ultrasound and theoretically allows transvaginal sonography (TVS) to discriminate benign from malignant adnexal masses.

Methods

Women (n = 264) scheduled for surgical removal of at least one ovary in five centres were included. Preoperative three-dimensional (3D)-TVS was performed and the voxel data were analysed by the new technology. The findings at 3D-TVS, serum CA125 levels and the TVS-based diagnosis were compared with histology. Cancer was deemed present when invasive or borderline cancerous processes were observed histologically.

Results

Among 375 removed ovaries, 141 cancers (83 adenocarcinomas, 24 borderline, 16 cases of carcinomatosis, nine of metastases and nine others) and 234 non-cancerous ovaries (107 normal, 127 benign tumours) were histologically diagnosed. The new computer-aided technology correctly identified 138/141 malignant lesions and 206/234 non-malignant tissues (98% sensitivity, 88% specificity). There were no false-negative results among the 47 FIGO stage I/II ovarian lesions. Standard TVS and CA125 had sensitivities/specificities of 94%/66% and 89%/75%, respectively. Combining standard TVS and the new technology in parallel significantly improved TVS specificity from 66% to 92% (p < 0.0001).

Conclusions

Computer-aided quantification of backscattered ultrasound is a highly sensitive for the diagnosis of malignant ovarian masses.

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Acknowledgements

The following investigators are members of the Ovarian HistoScanning Clinical Study Group:

B Lauratet B, JP Lefranc, PA Grenier: La Pitié—Salpêtrière Hospital, AP—HP, UPMC, Paris, France

K Schedvins K: Karolinska Hospital, Stockholm, Sweden

R di Pace R, D Franchi, M Bellomi, A Maggioni: European Institute of Oncology, Milan, Italy

R Mashiach, I Meizner: Rabin Medical Centre, Petah Tikva, Israel

A Schneider, J Lange: Hospital La Charité, Berlin, Germany

AS Absil, M Solnick, P Hennebert, AR Grivegnée: Jules Bordet Institute, Brussels, Belgium

R Nir, C Soviany: Advanced Medical Diagnostics, SA/NV, Drève Richelle, 161, 1410 Waterloo, Belgium

Author information

Authors and Affiliations

  1. La Pitié Salpétrière Hospital, APHP, UPMC, Paris, France

    Olivier Lucidarme & Jean-Paul Akakpo

  2. Karolinska Hospital, Stockholm, Sweden

    Seth Granberg

  3. Akershus University Hospital, Oslo, Norway

    Seth Granberg

  4. European Institute of Oncology, Milan, Italy

    Mario Sideri

  5. Rabin Medical Centre, Petah Tikva, Israel

    Hanoch Levavi

  6. Hospital La Charité, Berlin, Germany

    Achim Schneider

  7. International Prevention Research Institute (iPRI), Lyon, France

    Philippe Autier

  8. Advanced Medical Diagnostics, Waterloo, Belgium

    Dror Nir

  9. Jules Bordet Institute, Brussels, Belgium

    Harry Bleiberg

  10. Service de Radiologie Générale, Hôpital Pitié-Salpêtrière, 47/83, boulevard de l’Hôpital, 75651, Paris cedex 13, France

    Olivier Lucidarme

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  1. Olivier Lucidarme
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  2. Jean-Paul Akakpo
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  3. Seth Granberg
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for the Ovarian HistoScanning Clinical Study Group

Corresponding author

Correspondence to Olivier Lucidarme.

Additional information

Members of the Ovarian HistoScanning Clinical Study Group are listed in the Acknowledgements

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Lucidarme, O., Akakpo, JP., Granberg, S. et al. A new computer-aided diagnostic tool for non-invasive characterisation of malignant ovarian masses: results of a multicentre validation study. Eur Radiol 20, 1822–1830 (2010). https://doi.org/10.1007/s00330-010-1750-6

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  • DOI: https://doi.org/10.1007/s00330-010-1750-6

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