Here is the list of publications related to LIFEx software and texture analysis.

  • 2018:
    • P Blanc-Durand, A Van Der Gucht, N Schaefer, E Itti, J O. Prior. Automatic lesion detection and segmentation of 18F-FET PET in gliomas: A full 3D U-Net convolutional neural network study. Plos One April 13, 2018 (link)
    • M Kirienko M, L Cozzi, A Rossi, E Voulaz, L Antunovic, A Fogliata, A Chiti, M Sollini. Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions. Eur J Nucl Med Mol Imaging. 2018 Apr 6. doi: 10.1007/s00259-018-3987-2. (link)
    • V Nardone, P Tini, S Croci, SF Carbone, L Sebaste, T Carfagno, G Battaglia, P Pastina, G Rubino, MA Mazzei, L Pirtoli. 3D bone texture analysis as a potential predictor of radiationinduced insufficiency fractures. Quant Imaging Med Surg 2018;8(1):14-24 (link)
    • C Caramella, A Allorant, F Orlhac, F Bidault, B Asselain, S Ammari, P Jaranowski, A Moussier, C Balleyguier, N Lassau, S Pitre-Champagnat. Can we trust the calculation of texture indices of CT images? A phantom study. Med Phys. 2018 Feb 14. doi: 10.1002/mp.12809 (link)
    • V Nardone, P Tini, C Nioche, MA Mazzei, T Carfagno, G Battaglia, P Pastina, R Grassi, L Sebaste, L Pirtoli. Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT. Radiol Med. 2018 Jan 24. doi: 10.1007/s11547-017-0850-7 (link)
    • F Orlhac, S Boughdad, C Philippe, H Stalla-Bourdillon, C Nioche, L Champion, M Soussan, F Frouin, V Frouin, I Buvat. A post-reconstruction harmonization method for multicenter radiomic studies in PET. J Nucl Med. 2018  doi: 10.2967/jnumed.117.199935. [Epub ahead of print] (link)
    • M Kirienko, L Cozzi, L Antunovic, L Lozza, A Fogliata, E Voulaz, A Rossi, A Chiti, M Sollini ; Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery. Eur J Nucl Med Mol Imaging 45:207-217, 2018 (link)
    • N Aide, M Talbot, C Fruchart, G Damaj, C Lasnon ; Diagnostic and prognostic value of baseline FDG PET/CT skeletal textural features in diffuse large B cell lymphoma. Eur J Nucl Med Mol Imaging. 2018;45(5):699-711 (link)
    • A Schernberg, S Reuze, F Orlhac, I Buvat, L Dercle, R Sun, E Limkin, A Escande, C Haie-Meder, E Deutsch, C Chargari, C Robert ; A score combining baseline neutrophilia and primary tumor SUVpeak measured from FDG PET is associated with outcome in locally advanced cervical cancer ; Eur J Nucl Med Mol Imaging. 2018;45(2):187-195. doi: 10.1007/s00259-017-3824-z (link)
  •  2017:
    • L Cozzi, N Dinapoli†, A Fogliata, WC Hsu, G Reggiori, F Lobefalo, M Kirienko, M Sollini, D Franceschini, T Comito, C Franzese, Ma Scorsetti and PM Wang ; Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy. BMC Cancer 2017 17:829 (link)
    • F Orlhac, C Nioche, M Soussan, I Buvat ; Understanding changes in tumor textural indices in PET: a comparison between visual assessment and index values in simulated and patient data. J Nucl Med 2017; 58:387–392: (link)
    • S Reuzé, F Orlhac, C Chargari, C Nioche, E Limkin, F Riet, A Escande, C Haie-Meder, L Dercle, S Gouy, I Buvat, E Deutsch, C Robert ; Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners. Oncotarget. 2017; 8(26):43169-43179 (link)
    • M Sollini, L Cozzi, G Pepe, L Antunovic, A Lania, L Di Tommaso, P Magnoni, PA Erba,M Kirienko ; [18F]FDG-PET/CT texture analysis in thyroid incidentalomas: preliminary results. European Journal of Hybrid Imaging1:3 (link)
    • V Nardone, P Tini, C Nioche, M Biondi, L Sebaste, MA Mazzei, F Banci Buonamici, L Pirtoli ; Texture analysis of parotid gland as a predictive factor of radiation induced xerostomia: A subset analysis. Radiother Oncol. 2017 Feb;122(2):321. doi: 10.1016/j.radonc.2016.09.004 (link)
  • 2016:
    • F Orlhac, B Thézé, M Soussan, R Boisgard, I Buvat ; Multiscale texture analysis: from 18F-FDG PET images to pathological slides. J Nucl Med 57: 1823-1828, 2016 (link)
    • O Diop, EAL Bathily, B Ndong, G Mbaye, RS Senghor, W Sow-Diop, M Soumboundou, LAD Diouf, AR Djiboune, PM Sy, M Diarra, O Ndoye, M Mbodj, S Seck-Gassama ; Etude de la robustesse des statistiques de premier ordre dans la discrimination des ganglions malins et benins dans le cancer du col de l'utérus. Journal des Sciences, I.S.S.N 0851 – 4631 (link)
  •  2015:
    • F Orlhac, M Soussan, K Chouahnia, E Martinod, I Buvat ; 18F-FDG PET-derived textural indices reflect tissue-specific uptake pattern in non small cell lung cancer. Plos One 10(12):e0145063, 2015 (link)
    • I Buvat, F Orlhac, M Soussan ; Tumor texture analysis in PET: where do we stand? J Nucl Med 56: 1642-1644, 2015 (link)
  •  2014:
    • M Soussan, F Orlhac, M Boubaya, L Zelek, M Ziol, V Eder, I Buvat ; Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer. Plos One 9: e94017, 2014 (link)
    • F Orlhac, M Soussan, JA Maisonobe, CA Garcia, B Vanderlinden, I Buvat ; Tumor texture analysis in 18F-FDG-PET: relationships between texture parameters, histogram indices, SUVs, metabolic volumes and total lesion glycolysis. J Nucl Med 55: 414-422, 2014 (link)

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