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Publications 2025 - Review / Others

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7 hours 47 minutes ago #19 by christophe.nioche
Publications 2025 - Review / Others was created by christophe.nioche
Review (13):
  1. LIFEx-MTV: Tasevski Slavko , Treglia Giorgio , Marin Andreea , Bertagna Francesco , Albano Domenico. The prognostic role of maximum tumor dissemination derived by PET/CT in oncological diseases: a systematic review. Frontiers in Medicine, Volume 12 - 2025, 2026. doi.org/10.3389/fmed.2025.1726567
  2. LIFEx-texture: Faizan Farooq , Mohit Sharma, Khursheed Ahmed, Srishti Bhardwaj and Arti. Advancements in Oncological Dynamic Contrast-Enhanced Mri: A Review and Critical Analysis of Prior Studies. INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING, MANAGEMENT & APPLIED SCIENCE (IJLTEMAS). ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XII, December 2025 . doi.org/10.51583/IJLTEMAS.2025.1412000010
  3. LIFEx-texture: Rao SS, Vidya R. Artificial Intelligence in Breast Cancer Diagnosis and Management. Br J Hosp Med. 2025.  doi.org/10.12968/hmed.2024.0786
  4. LIFEx-texture: Flaiban, E.; Orhan, K.; Gonçalves, B.C.; Lopes, S.L.P.d.C.; Costa, A.L.F. Radiomics in Action: Multimodal Synergies for Imaging Biomarkers. Bioengineering 2025, 12, 1139.  doi.org/10.3390/bioengineering12111139
  5. LIFEx-texture: Falcone, R.; Verkhovskaia, S.; Di Pietro, F.R.; Scianni, C.; Poti, G.; Morelli, M.F.; Marchetti, P.; De Galitiis, F.; Sammarra, M.; Cavallo, A.U. Application of Radiomics in Melanoma: A Systematic Review and Meta-Analysis. Cancers 2025, 17, 3130.  doi.org/10.3390/cancers17193130
  6. LIFEx-texture: Krzysztof Żerdziński, Michał Gałuszewski, Julita Janiec, Kamil Jóźwik, Paweł Łajczak, Bartłomiej Jurek. Révolution in nuclear medicine: How Artificial Intelligence is transforming the diagnosis and treatment of cancer - A review of the last literature ( link )
  7. LIFEx-texture: Namdar, K., Wagner, M.W., Ertl-Wagner, B.B. et al. Open-radiomics: a collection of standardized datasets and a technical protocol for reproducible radiomics machine learning pipelines. BMC Med Imaging 25, 312 (2025).  doi.org/10.1186/s12880-025-01855-2
  8. LIFEx-texture: Zhang L, Li D, Su T, Xiao T, Zhao S. Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis. J Med Internet Res 2025;27:e72420 doi.org/10.2196/72420
  9. LIFEx-texture: Chilaca-Rosas, M.F., Contreras-Aguilar, M.T., Pallach-Loose, F. et al. Systematic review and epistemic meta-analysis to advance binomial AI-radiomics integration for predicting high-grade glioma progression and enhancing patient management. Sci Rep 15, 16113 (2025).  doi.org/10.1038/s41598-025-98058-0
  10. LIFEx-texture: Mohammadzadeh I, Hajikarimloo B, Niroomand B, Faizi N, Faizi N, Habibi MA, Mohammadzadeh S, Soltani R, Artificial Intelligence based radiomic model in Craniopharyngiomas: A Systematic Review and Meta-Analysis on Diagnosis, Segmentation, and Classification, World Neurosurgery (2025), doi: doi.org/10.1016/j.wneu.2025.124050
  11. LIFEx-texture: Asaf Raza, Antonella Guzzo, Michele Ianni, Rosamaria Lappano, Alfredo Zanolini, Marcello Maggiolini, Giancarlo Fortino. Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis. Computer Methods and Programs in Biomedicine. 2025, 108768, ISSN 0169-2607,  doi.org/10.1016/j.cmpb.2025.108768
  12. LIFEx-texture: Salvatore Pezzino, Tonia Luca, Mariacarla Castorina, Stefano Puleo, Sergio Casorina. Current Trends and Emerging Themes in Utilizing Artificial Intelligence to Enhance Anatomical Diagnostic Accuracy and Efficiency in Radiotherapy.  Salvatore Pezzino et al 2025 Prog. Biomed. Eng. doi.org/10.1088/2516-1091/adc85e
  13. LIFEx-texture: Keshavarz, Pedram et al. Prediction of treatment response and outcome of transarterial chemoembolization in patients with hepatocellular carcinoma using artificial intelligence: A systematic review of efficacy. European Journal of Radiology, Volume 0, Issue 0, 111948.  doi.org/10.1016/j.ejrad.2025.111948
Others (38):
  1. LIFEx-texture: Anna D. Darenskaya, Bela M. Medvedeva, Tigran G. Gevorkyan, Alexander V. Petrovsky, Iuliia V. Molostova. Texture analysis of MR imaging for hepatocellular cancer diagnosis: Reality and prospects (literature review). Voprosy Onkologii = Problems in Oncology. 2025; 71(6): 1461-1476. doi.org/10.37469/0507-3758-2025-71-6-OF-2405
  2. LIFEx-texture: 690P Radiomics and artificial intelligence in the differentiation of jaw bone tumors on computed tomography. Abdullayeva, L.S. Annals of Oncology, Volume 36, S2009 doi.org/10.1016/j.annonc.2025.10.1128
  3. LIFEx-main: Anna D. Darenskaya, Bela M. Medvedeva, Tigran G. Gevorkyan, Alexander V. Petrovsky, Iuliia V. Molostova. Texture Analysis of MR Imaging for Hepatocellular Cancer Diagnosis: Reality and Prospects (Literature Review). Вопросы онкологии, 2025. Том 71, № 6 УДК 616.36-006.  doi.org/10.37469/0507-3758-2025-71-6-OF-2405
  4. LIFEx-texture: Kasapoğlu B., Erdinç Gündüz N., Barış M. M., Yarol R. C., Şahin E., Demir T., Keskinoğlu P., Akalın E. Does quantitative ultrasonographic analysis performed with artificial intelligence methods contribute to the diagnosis of lipedema? a pilot preliminary study. 2025 Lipedema World Congress, Rome, Italy, 5 - 08 November 2025, pp.225-226 ( link )
  5. LIFEx-texture: Nitin Gupta. Abstract A014: Prognostic value of tumor asphericity on initial staging. Clin Cancer Res (2025) 31 (23_Supplement): A014.  doi.org/10.1158/1557-3265.EARLYONSETCA25-A014
  6. LIFEx-texture: 松下, 知樹, 新家, 崇義, 西庄, 俊彦, 西良, 浩一, 坂東, 良美, 上原, 久典, 原田, 雅史, 2025, The Diagnostic Ability of Texture Analysis in MR Imaging for Neurogenic Tumors: Tokushima University Faculty of Medicine, 367–374 p. doi.org/10.2152/jmi.72.367
  7. LIFEx-MTV: Palivela Dhanusree, Sameer Taywade, Rajesh Kumar. ABAOCNMB165: Advancing from Perception to Precision: FDG PET/CT Radiomics Signatures Capture Histologic Grade and Sarcomatoid differentiation in patients with RCC. Abstracts of AOCNMB and SNMICON 2025. Indian Journal of Nuclear Medicine 40(Suppl 1):p S1-S121, December 2025. doi.org/10.4103/ijnm.ijnm_182_25
  8. LIFEx-MTV: Sreelakshmi Sujith, Melvika Pereira, Natasha Singh, Divya Shivdasani. ABAOCNMB181: A New Era of Digital Biopsy - Prediction of hormone receptor and ki67 status of breast cancer using 18-F FDG PET-CT radiomics based machine learning. Abstracts of AOCNMB and SNMICON 2025. Indian Journal of Nuclear Medicine 40(Suppl 1):p S1-S121, December 2025.  doi.org/10.4103/ijnm.ijnm_182_25
  9. LIFEx-MTV: Jules Zhang-Yin, Anne Ségolène Cottereau, Romain Ould-Ammar, Loïc Chartier, Romain Ricci, Catherine Thieblemont, David Sibon, Olivier Casasnovas, Loic Ysebaert, Gandhi Damaj, Stephanie Guidez, Gian Matteo Pica, Marc Andre, Philippe Gaulard, Marie-Helene Delfau-Larue, Franck Morschhauser, Richard Delarue, Vincent Camus, Emmanuel Bachy, Prognostic value of baseline metabolic tumor volume from lysa ro-CHOP trial inpatients with previously untreated peripheral T-cell lymphoma. Blood, Volume 146, Supplement 1, 2025, Page 894, ISSN 0006-4971,  doi.org/10.1182/blood-2025-894 .
  10. LIFEx-texture: A Dias. Advanced presentation of AI model performance in the QuantImage medical image analysis web platform - 2025 ( link )
  11. LIFEx-texture: Khvastochenko GI, Bryukhov VV, Krotenkova MV. Textural Analysis and Radiomics in the Diagnosis of Multiple Sclerosis: A Review. Digital Diagnostics. 2025;6(4):XXX–XXX.  doi.org/10.17816/DD656073
  12. LIFEx-texture: Yue Wang, Xue Wang, Xin-Yun Huang, Hong-Mei Jing, Song-Fu Jiang, He Li, Rong-Ji Mu,Qing Shi, Di Fu, Zhuo-Han Li, Hong-Mei Yi, Bin-Shen Ouyang, Biao Li, Fu-Hua Yan, Ting Niu, Shu Cheng, Li Wang, Ning Wen, Peng-Peng Xu and Wei-Li Zhao. A prognostic index integrating deep learning baseline PET/CT biomarkers and multi-omics profiling in diffuse large B cell lymphoma. Cell Reports Medicine 6, 102452, November 18, 2025 © 2025 Published by Elsevier Inc.  www.cell.com/cell-reports-medicine/pdfEx...2666-3791(25)00525-7
  13. LIFEx-texture: D Arzur, T Marin, T Horowitz, A Kas, G El Fakhri et a. Multicenter PET Image Harmonization Using Style-Guided CycleGAN in Primary Central Nervous System Lymphoma: InStyleGAN. Predictive Intelligence in Medicine: 8th International Workshop, PRIME 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings ( link ).
  14. LIFEx-texture: Zhang, Y., Cai, J., Cui, C. et al. Predicting breast cancer response to neoadjuvant therapy by integrating radiomic and deep-learning features from early-and-peak phases of DCE-MRI. BMC Cancer 25, 1747 (2025).  doi.org/10.1186/s12885-025-15095-8
  15. LIFEx-main: Zeel Modi, Nadera Sweiss, Adam E. Mikolajczyk, Christen Vagts, Christian Ascoli. Association of Liver Enzymes With 18FDG PET/CT Uptake in Sarcoidosis Patients. The American Journal of Gastroenterology. Vol 120 | Suppl. | October 2025  journals.lww.com/ajg/fulltext/2025/10002...with_18fdg.2439.aspx
  16. LIFEx-texture: Su, Jie-Min & Zheng, Qing-Zhong & Huang, Wen-Rong & Deng, Jing & Wu, Jun & Lu, Hong-Quan. (2021). Prognostic Value of 18F-FDG PET/CT Metabolic Parameters in Patients with Diffuse Large B-Cell Lymphoma. Zhongguo shi yan xue ye xue za zhi. 29. 1181-1186.  doi.org/10.19746/j.cnki.issn.1009-2137.2021.04.025
  17. LIFEx-texture: He Chao, Zhou Yeye, Zhang Bin, Deng Shengming. A Cohort Study of the Prognostic Value of 18F-FDG PET/CT Metabolic Parameters in Patients with Diffuse Large B-Cell Lymphoma Receiving CAR-T Therapy. CHINA ONCOLOGY 2025 Vol.35 No.8. doi.org/10.19401/j.cnki.1007-3639.2025.08.002
  18. LIFEx-texture: JACOB A, BÉZY-WENDLING J,  FANG Z, KACHENOURA A, KARFOUL A, ALBERA L, SAULEAU P, LE BOUQUIN JEANNÈS R. Approche multimodale pour le diagnostic de la maladie de Parkinson : IRM anatomique et EEG. Univ Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France ( link )
  19. LIFEx-texture: Pierfrancesco Novielli, Donato Romano, Michele Magarelli, Pierpaolo Di Bitonto, Roberto Bellotti and Sabina Tangaro. Bridging Structural and Functional Imaging: Integrated PET/CT Radiomics with Explainable Machine Learning. rd World Conference on eXplainable Artificial Intelligence: July 09–11, 2025, Istanbul, Turkey. ceur-ws.org/Vol-4017/paper_22.pdf
  20. LIFEx-texture: Radiomics zur Vorhersage der portalvenösen Tumorthrombose bei Patienten mit HCC, Mira Schnier aus Freiburg im Breisgau thesis. link
  21. LIFEx-texture: Mohammad R. Salmanpour, and al. Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging.  arxiv.org/pdf/2507.16065
  22. LIFEx-texture: Luboš Řehounek, Přírodovědecká fakulta, Masarykova univerzita, Ústav fyziky kondenzovaných látek. Thesis. Deep Learning in PET/CT Image Processing. 2024 ( link )
  23. LIFEx-texture: Aron Österlund. Bachelor’s thesis 2025. A systematic review on software tools for CT- and MRI-based body composition analysis ( link )
  24. LIFEx-texture: Charlotte Loisel, Julie Auriac, Fanny Orlhac, Manuel Pires, Romain-david Seban, Josef Yu, Marcus Hacker, Lalith kumar Shiyam sundar, Thomas Beyer and Irene Buvat. Reproducibility of the metabolic network identified using whole-body [18F]FDG-PET/CT in healthy women. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 251365; jnm.snmjournals.org/content/66/supplement_1/251365.abstract
  25. LIFEx-texture: Charlotte Loisel, Julie Auriac, Fanny Orlhac, Manuel Pires, Romain-david Seban, Josef Yu, Marcus Hacker, Lalith kumar Shiyam sundar, Thomas Beyer and Irene Buvat. Comparison of inter-organ metabolic networks between healthy females and breast cancer patients based on whole-body [18F]FDG-PET/CT. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 251361;  jnm.snmjournals.org/content/66/supplement_1/251361.abstract
  26. LIFEx-texture: Hugo Lopez, Hornella Fokem fosso, Che M'vondo, Aurélie Bertaut, Magali Rouffiac, Jihane Boustani, Fanny Orlhac, Christophe Nioche, Gilles Crehange and Irene Buvat. Clinico-radiomic models using pre-treatment [18F]-FDG PET/CT predict outcome in esophageal cancers treated with exclusive chemoradiotherapy. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 251588; jnm.snmjournals.org/content/66/supplement_1/251588.abstract
  27. LIFEx-texture: Monica Luo, Hamid Abdollahi, Fereshteh Yousefirizi, Sara Harsini and Arman Rahmim. Lung Cancer Radiopathomics: Correlating PET/CT Radiomics and Histopathological Features in Lung Adenocarcinoma and Squamous Cell Carcinoma. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 251687;  jnm.snmjournals.org/content/66/supplement_1/251687.abstract
  28. LIFEx-texture: Pooja Dwivedi, Sagar Barage, Ashish Jha, Rajshri Singh, Sayak Choudhury, Archi Agrawal and Venkatesh Rangarajan. Effect of ComBat Harmonization in PET-Based Radiomic Biomarkers for Tumor Phenotyping. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 25133;  jnm.snmjournals.org/content/66/supplement_1/25133.abstract
  29. LIFEx-texture: Tiancheng Li. Development and Validation of a Machine Learning Model Using Preoperative 18F-PSMA PET/MR to Predict Biochemical Recurrence-Free Survival After Radical Prostatectomy. Journal of Nuclear Medicine June 2025, 66 (supplement 1) 251341;  jnm.snmjournals.org/content/66/supplement_1/251341.abstract
  30. LIFEx-Texture: Hubert Beaumont, Emilie Khayat, Alexandre Thinnes, and Antoine Iannessi. Technical performance of the L3 Skeletal Muscle Index in CT.  Journal of Clinical Oncology Volume 43, Number 16_suppl doi.org/10.1200/JCO.2025.43.16_suppl.e2407
  31. LIFEx-Texture: Filippo Gustavo Dall'Olio, Wael Zrafi, Adsaya Rathakrishnan, Maeva Moreau, Rebecca Ibrahim, Matthieu Texier, Adrien Laville, Damien Vasseur, Patrick Saulnier, Amaury Daste, Karim Benihoud, Pierre Busson, Ivan Bieche, Clemence Toullec, Mariana Iacob, Roger Sun, Anne Auperin, Laure Monard, Ludovic Lacroix, and Caroline Even. ctDNA tumor fraction (TF) to predict response to nivolumab in recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC): An analysis of the multicentric phase 2 TOPNIVO trial. Journal of Clinical Oncology. Volume 43, Number 16_suppl  doi.org/10.1200/JCO.2025.43.16_suppl.6047
  32. LIFEx-texture: Lorenzo Tucci, Giulio Vara, Antonio De Leo, Kassiani Skordilis, Lisa James, Cristina Mosconi, Balraj Dhesi, Dario De Biase, Juliane Lippert, Abubaker Mohamed, Guido Di Dalmazi, Cristina L Ronchi. Radiogenomics pilot study in adrenocortical carcinoma: assessing the relationship between genetic background and computerized tomography texture. Endocrine Abstracts (2025) 110 P464.   doi.org/10.1530/endoabs.110.P464
  33. LIFEx-texture: Tan Qianqian, Zhao Lianjun, He Jian, Lai Ruihe. Study on the assessment of intratumoral metabolic heterogeneity parameters of metastatic lesions by 18F-FDG PET/CT for predicting the prognosis of patients with malignant melanoma[J]. Int J Radiat Med Nucl Med, 2025, 49(2): 78-86. DOI: 10.3760/cma.j.cn121381-202408031-00513
  34. LIFEx-texture: HangYu Watson, Seher Berzingi, Karthik Seetharam, Samuel A. Mensah, Syed Ahmad and Brijesh D. Patel. Myocardial tissue texture improves diagnostic accuracy of echocardiogram to diagnosis of hypertrophic cardiomyopathy. JACC. 2025 Apr, 85 (12_Supplement) 2575.  www.jacc.org/doi/abs/10.1016/S0735-1097%2825%2903059-1
  35. LIFEx-texture:TERZI ATHINA Marina. Radiogenomic Analysis of Lung Cancer. MSc program “Biomedical Engineering and Technology”.  polynoe.lib.uniwa.gr/xmlui/bitstream/han...6/Terzi_bmet2305.pdf
  36. LIFEx-texture: Yunus Soleymani, Farahnaz Aghahosseini, Peyman Sheikhzadeh. Correlation of radiomics features extracted from nuclear medicine images with lesion metabolism in patients with colon cancer. February 2025Tehran University Medical Journal 82(5).  link
  37. LIFEx-texture: Malhaire C thesis. Optimization of the Prediction of Complete Response to Neoadjuvant Chemotherapy in Breast Cancer by Breast MRI : Contributions of Semantic Descriptors, Radiomics, and Segmentation Methods. HAL Id: tel-04931114.  theses.hal.science/tel-04931114v1
  38. LIFEx-texture: S. Gülbahar Ates, B. B. Demirel, E. Kekilli, E. Öztürk, G. Uçmak. Primary Tumor Heterogeneity on Pre-treatment [68Ga]Ga-PSMA PET/CT for the Prediction of Biochemical Recurrence in Prostate Cancer. Revista española de medicina nuclear e imagen molecular, ISSN 2253-654X, Vol. 43, Nº. 6 (Noviembre-Diciembre), 2024, págs. 4-4. dialnet.unirioja.es/ejemplar/686513

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