Modelo radiómico con PSMA-PET para la discriminación de pacientes con cáncer de próstata de alto riesgo

Autores/as

  • Montserrat Carles Fariña La Fe Health Research Institute, Biomedical Imaging Research Group (GIBI230-PREBI) and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain https://orcid.org/0000-0003-2401-8240
  • Constatinos Zamboglou Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany
  • Tobias Fechter Department of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany
  • Selina Kiefer Institute for Surgical Pathology, Medical Center – University of Freiburg, Faculty of Medicine. University of Freiburg, Germany
  • Kathrin Reichel Department of Urology, Medical Center – University of Freiburg, Faculty of Medicine. University of Freiburg, Germany
  • Martin Werner Institute for Surgical Pathology, Medical Center – University of Freiburg, Faculty of Medicine. University of Freiburg, Germany
  • Cordula A Jilg Department of Urology, Medical Center – University of Freiburg, Faculty of Medicine. University of Freiburg, Germany
  • Luis Martí-Bonmatí https://orcid.org/0000-0002-8234-010X
  • Dimos Baltas Department of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany
  • Michael Mix Department of Nuclear Medicine, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany
  • Anca L. Grosu Department of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany

DOI:

https://doi.org/10.37004/sefm/2022.23.2.002

Palabras clave:

Cáncer de próstata, PSMA-PET, modelos radiómicos, puntaje Gleason

Resumen

La estimación del puntaje Gleason (PG) en pacientes con cáncer de próstata (PCa) mediante modelos radiómicos es de especial interés por ser una alternativa no invasiva a la biopsia, para estratificar el nivel de riesgo y ayudar en la elección del tratamiento. Nuestro objetivo es estimar el PG mediante un modelo radiómico con imágenes [68Ga]-antígeno de membrana específico de la próstata (PSMA, Prostate Specific Membrane Antigen) de tomografía por emisión de positrones (PET, Positron Emission Tomography). Para la cohorte de entrenamiento (20 pacientes), además de la segmentación manual, se disponía de corregistro histopatológico, que se estableció como segmentación ideal para la confirmación de los resultados. Los modelos radiómicos fueron adicionalmente validados para la segmentación manual en una segunda cohorte (40 pacientes). Se calcularon 133 características radiómicas y primero se evaluó en maniquíes experimentales la dependencia intrínseca con el volumen y con los equipos híbridos de PET y tomografía computarizada (TC) y posteriormente en pacientes, se comparó sus valores dentro y fuera del tumor y la caracterización del PG. Se utilizó la prueba de los rangos con signo de Wilcoxon, la correlación de Spearman y la regresión logística como métodos de análisis. Los resultados mostraron 50 características radiómicas intrínsecamente independientes del volumen y con capacidad para discriminar el tumor independientemente de la segmentación utilizada. El PG se estratificó (PG < 8 vs PG ≥ 8) mediante una característica radiómica con área-bajo-la-curva (AUC, area-under-the-curve) de 0.91/0.84 (cohorte entrenamiento/validación) y con una firma radiómica (AUC de 0.93/0.78). Nuestros resultados avalan la capacidad del modelo radiómico con 68Ga- PSMA-PET para estratificar el PG en PCa.

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Publicado

2022-11-15

Cómo citar

Carles Fariña, M. ., Zamboglou, C., Fechter, T., Kiefer, S. ., Reichel, K. ., Werner, M. ., Jilg, C. A., Martí-Bonmatí, L. ., Baltas, D., Mix, M., & Grosu , A. L. . (2022). Modelo radiómico con PSMA-PET para la discriminación de pacientes con cáncer de próstata de alto riesgo. Revista De Física Médica, 23(2), 21–37. https://doi.org/10.37004/sefm/2022.23.2.002

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