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Prostate Cancer Detection: Performance of Radiomics Analysis in Multiparametric MRI

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Image Analysis and Processing - ICIAP 2023 Workshops (ICIAP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14366))

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Abstract

The purpose of the study was to evaluate the performance of radiomics analysis of MR images for the detection of prostate cancer. The radiomics analysis was conducted using axial T2-weighted images from 49 prostate cancers. The study employs a sophisticated hybrid descriptive-inferential method for the meticulous selection and reduction of features, followed by discriminant analysis to construct a robust predictive model. Among 71 radiomics features, original_glrlm_ShortRunLowGrayLevelEmphasis demonstrated exemplary performance in differentiating between the whole prostate gland and prostate cancer. It had an AUROC of 68.46 (95% CI 0.544 – 0.824; p = 0.022), sensitivity of 76.25%, specificity of 73.15%, and accuracy of 71.02%. Radiomic analysis of T2 weighted MR images was demonstrated to have clinical application in prostate cancer detection, paving the way for improved diagnostic procedures and tailor-made treatment plans for prostate cancer patients.

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Authors and Affiliations

  1. Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, Molecular and Clinical Medicine, University of Palermo, 90127, Palermo, Italy

    Muhammad Ali, Viviana Benfante, Domenico Di Raimondo & Antonino Tuttolomondo

  2. Ri.MED Foundation, Via Bandiera 11, 90133, Palermo, Italy

    Muhammad Ali, Viviana Benfante, Leonardo Salvaggio & Giovanni Piraino

  3. Department of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, 90100, Palermo, Italy

    Giuseppe Cutaia, Leonardo Salvaggio, Sara Rubino, Marzia Portoghese, Marcella Ferraro & Giuseppe Salvaggio

  4. Department of Mathematics and Computer Science, University of Palermo, ViaArchirafi 34, 90123, Palermo, Italy

    Rosario Corso

  5. Department of Engineering, University of Palermo, 90100, Palermo, Italy

    Giovanni Piraino & Tommaso Ingrassia

  6. Department of Surgical, Oncological and Stomatological Sciences, Urology Section, University of Palermo, 90100, Palermo, Italy

    Gabriele Tulone, Nicola Pavan & Alchiede Simonato

Authors
  1. Muhammad Ali
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  2. Viviana Benfante
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  3. Giuseppe Cutaia
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  4. Leonardo Salvaggio
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  5. Sara Rubino
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  6. Marzia Portoghese
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  8. Rosario Corso
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  11. Gabriele Tulone
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  12. Nicola Pavan
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  13. Domenico Di Raimondo
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  14. Antonino Tuttolomondo
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  15. Alchiede Simonato
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  16. Giuseppe Salvaggio
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Corresponding author

Correspondence to Viviana Benfante .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Gian Luca Foresti

  2. University of Udine, Udine, Italy

    Andrea Fusiello

  3. University of York, York, UK

    Edwin Hancock

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Ali, M. et al. (2024). Prostate Cancer Detection: Performance of Radiomics Analysis in Multiparametric MRI. In: Foresti, G.L., Fusiello, A., Hancock, E. (eds) Image Analysis and Processing - ICIAP 2023 Workshops. ICIAP 2023. Lecture Notes in Computer Science, vol 14366. Springer, Cham. https://doi.org/10.1007/978-3-031-51026-7_8

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  • DOI: https://doi.org/10.1007/978-3-031-51026-7_8

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  • Online ISBN: 978-3-031-51026-7

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