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Prediction of therapy outcome

IMPACT Team: Image and models for the prediction of therapy outcome


Anticipating the effect of an action or a treatment implicates data analysis and/or the implementation of models explicitly representing the processes of therapy and their interactions with anatomo-physiological structures and functions. Modelling is both aimed at understanding complex pathophysiological phenomena and at optimising interventional strategy.

Prediction of response to radiation therapy

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Segmental maping of the rectum to identify a sub-region at risks of rectal bleeding

​PhD of:

  • A. Fargeas. Classification, Feature Extraction and Prediction of Side Effects after Prostate Cancer Radiotherapy.
  • R. Rios. Statistical Modeling of Bladder Motion and Deformation in Prostate Cancer Radiotherapy.
  • E. Mylona. From Global to Local Spatial Models for Improving Prediction of Urinary Toxicity Following Prostate Cancer Radiotherapy.
  • G. Roman Jimenez. Analyse Des Images De Tomographie Par Émission De Positons Pour La Prédiction De Récidive Des Cancers Du Col De L'utérus.
  • R. Mathieu. Prédiction du risque de récidive du cancer de prostate à partir d'une caractérisation multimodale.
  • J. Beaumont. Towards new means of performing multi T1 w contrast imaging and T1 mapping with the FLAWS magnetic resonance sequence.
  • P. Fontaine. Prédiction de la réponse à la radiothérapie à partir de l'extraction de caractéristiques des images multimodales dans un contexte radiomics.
  • C. Sosa Marrero. Modélisation et simulation numérique de croissance tumorale et réponse à la radiothérapie.
     

Selected publications:

  • Acosta O, Mylona E, Le Dain M, Voisin C, Lizee T, Rigaud B, Lafond C, Gnep K, De Crevoisier R. Multi-Atlas-Based Segmentation of Prostatic Urethra from Planning Ct Imaging to Quantify Dose Distribution in Prostate Cancer Radiotherapy. Radiotherapy and Oncology. 2017 Dec;125(3):492-9.
  • Acosta, O. and De Crevoisier, R., Beyond DVH: 2D/3D based dose comparison to assess predictors of toxicity, in Modelling Radiotherapy Side Effects: Practical Applications for Planning Optimisation, T. Rancati and C. Fiorino, Editors. 2019, CRC Press.
  • Aubert V, Acosta O, Rioux-Leclercq N, Mathieu R, Commandeur F, De Crevoisier R. In Silico Model to Simulate the Radiation Response at Various Fractionation from Histopathological Images of Prostate Tumors Proceedings of the IEEE 14th International Symposium on Biomedical Imaging; 2017; New York. Ieee;  p. 818-21.
  • Beaumont J, Acosta O, Devillers A, Palard-Novello X, Chajon E, De Crevoisier R, Castelli J. Voxel-Based Identification of Local Recurrence Sub-Regions from Pre-Treatment Pet/Ct for Locally Advanced Head and Neck Cancers. Ejnmmi Research. 2019 Sep;9(1):11.
  • Coloigner J, Fargeas A, Kachenoura A, Wang L, Drean G, Lafond C, Senhadji L, De Crevoisier R, Acosta O, Albera L. A Novel Classification Method for Prediction of Rectal Bleeding in Prostate Cancer Radiotherapy Based on a Semi-Nonnegative Ica of 3d Planned Dose Distributions. IEEE Journal of Biomedical and Health Informatics. 2015 May;19(3):1168-77.
  • Drean G, Acosta O, Lafond C, Simon A, De Crevoisier R, Haigron P. Interindividual Registration and Dose Mapping for Voxelwise Population Analysis of Rectal Toxicity in Prostate Cancer Radiotherapy. Medical Physics. 2016 Jun;43(6):2721-30.
  • Drean G, Acosta O, Ospina JD, Fargeas A, Lafond C, Correge G, Lagrange JL, Crehange G, Simon A, Haigron P, De Crevoisier R. Identification of a Rectal Subregion Highly Predictive of Rectal Bleeding in Prostate Cancer Imrt. Radiotherapy and Oncology. 2016 Jun;119(3):388-97.
  • Fargeas A, Acosta O, Arrango JDO, Ferhat A, Costet N, Albera L, Azria D, Fenoglietto P, Crehange G, Beckendorf V, Hatt M, Kachenoura A, De Crevoisier R. Independent Component Analysis for Rectal Bleeding Prediction Following Prostate Cancer Radiotherapy. Radiotherapy and Oncology. 2018 Feb;126(2):263-9.
  • Gnep K, Fargeas A, Gutierrez-Carvajal RE, Commandeur F, Mathieu R, Ospina JD, Rolland Y, Rohou T, Vincendeau S, Hatt M, Acosta O, De Crevoisier R. Haralick Textural Features on T-2-Weighted Mri Are Associated with Biochemical Recurrence Following Radiotherapy for Peripheral Zone Prostate Cancer. Journal of Magnetic Resonance Imaging. 2017 Jan;45(1):103-17.
  • Lafond C, Barateau A, N'Guessan J, Perichon N, Delaby N, Simon A, Haigron P, Mylona E, Acosta O, de Crevoisier R. Planning with Patient-Specific Rectal Sub-Region Constraints Decreases Probability of Toxicity in Prostate Cancer Radiotherapy. Frontiers in Oncology. 2020 Sep;10:11.
  • Leseur J, Roman-Jimenez G, Devillers A, Ospina-Arango JD, Williaume D, Castelli J, Terve P, Lavoue V, Garin E, Lejeune F, Acosta O, De Crevoisier R. Pre- and Per-Treatment 18f-Fdg Pet/Ct Parameters to Predict Recurrence and Survival in Cervical Cancer. Radiotherapy and Oncology. 2016 Sep;120(3):512-8.
  • Mylona E, Acosta O, Lizee T, Lafond C, Crehange G, Magne N, Chiavassa S, Supiot S, Arango JDO, Campillo-Gimenez B, Castelli J, De Crevoisier R. Voxel-Based Analysis for Identification of Urethrovesical Subregions Predicting Urinary Toxicity after Prostate Cancer Radiation Therapy. International Journal of Radiation Oncology Biology Physics. 2019 Jun;104(2):343-54.
  • Mylona E, Cicchetti A, Rancati T, Palorini F, Fiorino C, Supiot S, Magne N, Crehange G, Valdagni R, Acosta O, De Crevoisier R. Local Dose Analysis to Predict Acute and Late Urinary Toxicities after Prostate Cancer Radiotherapy: Assessment of Cohort and Method Effects. Radiotherapy and Oncology. 2020 Mar 27;147:40-9.
  • Rios R, De Crevoisier R, Ospina JD, Commandeur F, Lafond C, Simon A, Haigron P, Espinosa J, Acosta O. Population Model of Bladder Motion and Deformation Based on Dominant Eigenmodes and Mixed-Effects Models in Prostate Cancer Radiotherapy. Medical Image Analysis. 2017 May;38:133-49.
  • Roman-Jimenez G, De Crevoisier R, Leseur J, Devillers A, Ospina JD, Simon A, Terve P, Acosta O. Detection of Bladder Metabolic Artifacts in F-18-Fdg Pet Imaging. Computers in Biology and Medicine. 2016 Apr;71:77-85.
  • Sosa-Marrero C, de Crevoisier R, Hernandez A, Fontaine P, Rioux-Leclercq N, Mathieu R, Fautrel A, Paris F, Acosta O. Towards a Reduced in Silico Model Predicting Biochemical Recurrence after Radiotherapy in Prostate Cancer. IEEE Trans Biomed Eng. 2021 Jan 18;Pp.

Numerical simulation for computer assisted endovascular interventions

PhD of:

  • A. Dumenil. Fusion D'images Et De Modèles Pour Le Guidage D'interventions Endovasculaires.
  • A. Kaladji. Apport De L'assistance Par Ordinateur Lors De La Pose D'endoprothèse Aortique.
  • J. Gindre. Simulation Spécifique Patient De La Réponse Mécanique De La Structure Vasculaire à L'insertion D'outils Lors D'une Chirurgie EVAR.
  • P. Vy. Simulation Numérique Pour La Compréhension Et La Planification De La Pose De Valves Aortiques Par Voie Endovasculaire.

Selected publications:

  • Duménil A, Kaladji A, Castro M, Esneault S, Lucas A, Rochette M, Göksu C, Haigron P. Finite-Element-Based Matching of Pre- and Intraoperative Data for Image-Guided Endovascular Aneurysm Repair. IEEE Trans Biomed Eng. 2013 May;60(5):1353-62.
  • Dupont C, Kaladji A, Rochette M, Saudreau B, Lucas A, Haigron P. Numerical Simulation of Fenestrated Graft Deployment: Anticipation of Stent Graft and Vascular Structure Adequacy. Int J Numer Method Biomed Eng. 2021 Jan;37(1):e03409.
  • Gindre J, Bel-Brunon A, Kaladji A, Dumenil A, Rochette M, Lucas A, Haigron P, Combescure A. Finite Element Simulation of the Insertion of Guidewires During an Evar Procedure: Example of a Complex Patient Case, a First Step toward Patient-Specific Parameterized Models. International Journal for Numerical Methods in Biomedical Engineering. 2015 Jul;31(7):17.
  • Gindre J, Bel-Brunon A, Rochette M, Lucas A, Kaladji A, Haigron P, Combescure A. Patient-Specific Finite-Element Simulation of the Insertion of Guidewire During an Evar Procedure: Guidewire Position Prediction Validation on 28 Cases. IEEE Transactions on Biomedical Engineering. 2017 May;64(5):1057-66.
  • Kaladji A, Dumenil A, Castro M, Cardon A, Becquemin JP, Bou-Saïd B, Lucas A, Haigron P. Prediction of Deformations During Endovascular Aortic Aneurysm Repair Using Finite Element Simulation. Comput Med Imaging Graph. 2013 Mar;37(2):142-9.
  • Tomasi J, Le Bars F, Shao C, Lucas A, Lederlin M, Haigron P, Verhoye JP. Patient-Specific and Real-Time Model of Numerical Simulation of the Hemodynamics of Type B Aortic Dissections. Medical Hypotheses. 2020 Feb;135:13.
  • Vy P, Auffret V, Badel P, Rochette M, Le Breton H, Haigron P, Avril S. Review of Patient-Specific Simulations of Transcatheter Aortic Valve Implantation. International Journal of Advances in Engineering Sciences and Applied Mathematics. 2016 Mar;8(1):2-24.
  • Vy P, Auffret V, Castro M, Badel P, Rochette M, Haigron P, Avril S. Patient-Specific Simulation of Guidewire Deformation During Transcatheter Aortic Valve Implantation. International Journal for Numerical Methods in Biomedical Engineering. 2018 Jun;34(6):18.