Twitter Discord

Publications 2025 - Journal papers

More
8 hours 7 minutes ago #18 by christophe.nioche
Publications 2025 - Journal papers was created by christophe.nioche
Articles (149)
  1. LIFEx-texture: Anna Scavuzzo, Giovanni Pasini, Osvaldo G. Perez, Miguel A. Jimenez Rios, Marina Arenas Hernández, Roberto Pedrero-Piedras, Maria Delia Pérez Montiel, Nora Sobrevilla Moreno, Giorgio Russo and Alessandro Stefano. Radiomics-based machine learning models for predicting genomic alterations in metastatic prostate cancer using PSMA PET imaging: a pilot study. Scavuzzo et al. EJNMMI Reports (2025) 9:42.  doi.org/10.1186/s41824-025-00280-6
  2. LIFEx-texture: V. B. Orel, А. А. Chumak, V. E. Orel, A. Yu. Galkin, A. І. Tovstolytkin, A. G. Diedkov, V. V. Ostafiichuk, S. O. Mamilov, V. V. Shlykov, O. V. Ganich, O. Yo. Dasyukevich,O. Yu. Rykhalskyi, O. S. Ostapenko. Study of the combined effect of doxorubicin;loaded superparamagnetic nanoparticles and non;ionising electromagnetic irradiation on walker; 256 carcinosarcoma. ISSN 23048336. Проблеми радіаційної медицини та радіобіології = Problems of Radiation Medicine and Radiobiology. 2025. Iss. 30. doi.org/0.33145/2304A8336A2025A30A260A272
  3. LIFEx-texture: Nihat Köylüce, Mahmut Erkam Arslan. Lacrimal gland Ga-68 PSMA-11 PET/CT radiomic profile: a potential novel imaging biomarker in dry eye disease. Contact Lens and Anterior Eye, Volume 49, Issue 1, 2026, 102600, ISSN 1367-0484, doi.org/10.1016/j.clae.2025.102600
  4. LIFEx-texture: Almeda-Luna, E., Luna, J.M. & Ventura, S. Exploring free radiomics software tools: a multiparametric evaluation for cancer classification. BMC Med Imaging (2025). doi.org/10.1186/s12880-025-02115-z
  5. LIFEx-texture: Lorenzo Mercolli, William M. Steinberger, Tilman Läppchen, Michelle Amon, Carola Bregenzer, Maurizio Conti, Ângelo R. Felgosa Cardoso, Clemens Mingels, Paweł Moskal, Narendra Rathod, Hasan Sari, Ewa Ł. Stępień, Sabine Weidner, Axel Rominger, Kuangyu Shi, Robert Seifert. In vivo voxel-wise positronium lifetime imaging of thyroid cancer using clinically routine I-124 PET/CT. 10 December 2025. Elsevier.  doi.org/10.1016/j.eanmi.2025.100017
  6. LIFEx-texture: X. Boulvard Chollet, M.P. Garrastachu Zumarán, L.G. Romero Robles, A. Santapau Traveria, M.C. Albornoz Almada, R. Ramírez Lasanta, J.G. Pichel, R.C. Delgado Bolton. Evaluation of the diagnostic efficacy of [18F]FDG PET radiomic analysis for tumor
    differentiation in patients with non-small cell lung cancer. Revista Española de Medicina Nuclear e Imagen Molecular. 2025, 500250,ISSN 2253-654X, doi.org/10.1016/j.remn.2025.500250
  7. LIFEx-texture: Dai, J., Zou, Y., Wang, H. et al. 68Ga-FAPI and 18F-FDG PET/CT for predicting pathologic response and progression-free survival in locally advanced esophageal squamous cell carcinoma treated with neoadjuvant chemoradiotherapy. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07684-3
  8. LIFEx-texture: : L. Mercolli, W.M. Steinberger, T. Läppchen et al., In vivo voxel-wise positronium lifetime imaging of thyroid cancer using clinically routine I-124 PET/CT. EANM Innovation (2025), doi:  doi.org/10.1016/j.eanmi.2025.100017
  9. LIFEx-MTV: iang J, Lu G, Peng Q, Wang J and Zhang G (2025) Baseline PET/CT metabolic parameters in the double-expressor subtype of diffuse large B-cell lymphoma: development of a clinical–radiologic–pathologic predictive model. Front. Oncol. 15:1660516. doi.org/10.3389/fonc.2025.1660516
  10. LIFEx-MTV: Hua, Yua,b; Wang, Binc; Su, Qiana,b. The relationship between posttreatment 18F-fluorodeoxyglucose PET/computed tomography restaging and metabolic parameters with the prognosis of uterine cervical cancer. Nuclear Medicine Communications ():10.1097/MNM.0000000000002093, December 12, 2025. |  doi.org/10.1097/MNM.0000000000002093
  11. LIFEx-RTdose: Mostafa Rezaei et al 2026. Evaluating the robustness of dosiomics features over treatment planning parameters: a phantom-based study; Biomed. Phys. Eng. Express 12 015002
  12. LIFEx-texture: Dong, S., Feng, YN., Li, XY. et al. Preoperative non-invasive prediction of lymph node metastasis in cervical cancer using a multiparametric radiomics model based on transvaginal ultrasound. Abdom Radiol (2025).  doi.org/10.1007/s00261-025-05297-w
  13. LIFEx-texture: Xin, W., Wang, F., Lu, L. et al. Tumor metabolic heterogeneity based on 18F-FDG PET/CT is a predictor of outcome in diffuse large B-cell lymphoma. BMC Cancer 25, 1807 (2025).  doi.org/10.1186/s12885-025-15149-x
  14. LIFEx-texture: Lai, R., Jiang, Z., Sheng, D. et al. Prognostic value of a combined model integrating clinical and PET radiomics parameters in metastatic melanoma: A dual-center retrospective study. Ann Nucl Med (2025).  doi.org/10.1007/s12149-025-02133-5
  15. LIFEx-texture: Li, S., Zhang, X., Wang, X. et al. [18F]FDG PET/CT in combination with clinicopathological parameters for outcome prediction in high-grade soft tissue sarcoma undergoing surgical resection. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07637-w
  16. LIFEx-Main: D. Samaras, G. Agrotis, D. Tsivaka, M. Vakalopoulou, K. Vassiou, V. Tzortzis, M. Vlychou, I. Tsougos, Comparative evaluation of ADC and ADC ratio in differentiating Gleason Score 7 in prostate cancer imaging, European Journal of Radiology Open, Volume 15, 2025, 100710, ISSN 2352-0477,  doi.org/10.1016/j.ejro.2025.100710
  17. LIFEx-texture: Gleb I. Khvastochenko · Vasiliy V. Bryukhov · Marina V. Krotenkova. Textural analysis and radiomics in the diagnosis of multiple sclerosis. Digital Diagnostics. 2025.  doi.org/10.17816/DD656073
  18. LIFEx-texture: MA Elahmadawy, DH Gama El-din, SF Abdelhai et al. Can radiomics signatures and machine learning methods reinforce the revived role of 18F-NaF in metastatic bone disease? Asia Oceania Journal of Nuclear Medicine and Biology. 2025.  aojnmb.mums.ac.ir/article_26999.html
  19. LIFEx-MTV: Mirshahvalad, S.A., Kohan, A., Kulanthaivelu, R. et al. Added prognostic value of baseline pre-infusion 18F-FDG PET/CT in diffuse large B-cell lymphoma patients receiving chimeric antigen receptor T-cell therapy. Sci Rep 15, 39540 (2025). doi.org/10.1038/s41598-025-23159-9
  20. LIFEx-MTV: Zeyu Wang, Wei Han, Zhehao Lyu, Jiafu Wang, Xinyue Zhang, Mingzhen Wang, Menglu Wang, Peng Fu. A clinical study of the feasibility of early Al18F-fibroblast activation protein inhibitor-04 PET/CT scans. BJR, 2025, 00, 1–8. doi.org/10.1093/bjr/tqaf274
  21. LIFEx-texture: Kang, J., Kim, Y., Jeong, Y. et al. Development and validation of a LASSO-Based FDG PET/CT model for predicting colorectal adenoma in asymptomatic individuals undergoing colonoscopy. Ann Nucl Med (2025).  doi.org/10.1007/s12149-025-02122-8
  22. LIFEx-texture: Koyluce, Nihat; Abdulrezzak, Ummuhan; Tutus, Ahmet. Volumetric 68Ga-PSMA PET/CT analysis of bone metastasis subtypes in prostate cancer: correlation with prostate-specific antigen and International Society of Urological Pathology grade. Nuclear Medicine Communications 46(12):p 1240-1248, December 2025. |  doi.org/10.1097/MNM.0000000000002044
  23. LIFEx-Calcium: V Marcos Garces, S Minguez Diaz De Alda, H Merenciano-Gonzalez, M Perez-Pelegri, O Straka, J Gavara, C Bertolin-Boronat, N Perez, C Rios-Navarro, E De Dios, S Aulet-Manuel, J Canoves, J Sanchis, D Moratal, V Bodi, Incidental coronary artery calcification and cardiovascular risk stratification in the ICARUS registry, European Heart Journal, Volume 46, Issue Supplement_1, November 2025, ehaf784.3593, doi.org/10.1093/eurheartj/ehaf784.3593
  24. LIFEx-Main Zhao, H., Lyu, Z., Su, Y. et al. 18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients. Abdom Radiol (2025).  doi.org/10.1007/s00261-025-05282-3
  25. LIFEx-texture: Zeyu Wang, Wei Han, Zhehao Lyu, Jiafu Wang, Xinyue Zhang, Mingzhen Wang, Menglu Wang, Peng Fu. A clinical study of the feasibility of early Al18F-fibroblast activation protein inhibitor-04 PET/CT scans. Annals of Nuclear Medicine, 2025.  academic.oup.com/bjr/advance-article/doi.../bjr/tqaf274/8319996
  26. LIFEx-texture: Kang, J., Kim, Y., Jeong, Y. et al. Development and validation of a LASSO-Based FDG PET/CT model for predicting colorectal adenoma in asymptomatic individuals undergoing colonoscopy. Ann Nucl Med (2025).  doi.org/10.1007/s12149-025-02122-8
  27. LIFEx-MTV: Mirshahvalad, S.A., Kohan, A., Kulanthaivelu, R. et al. Added prognostic value of baseline pre-infusion 18F-FDG PET/CT in diffuse large B-cell lymphoma patients receiving chimeric antigen receptor T-cell therapy. Sci Rep 15, 39540 (2025).  doi.org/10.1038/s41598-025-23159-9
  28. LIFEx-main: Sajad Keshavarz, Elham Saeedzadeh, Dariush Sardari, Elnaz Jenabi-Haghparast, Hossein Arabi. A dual-validation 3D nnU-Net framework with harmonized preprocessing for robust DLBCL segamentation in PET/CT images. Machine Learning with Applications. Volume 22, 2025, 100788, ISSN 2666-8270,  doi.org/10.1016/j.mlwa.2025.100788
  29. LIFEx-texture: BS Diba, N Tasnim, M Hossain, AK Saha, MG Kibriya. and al. Federated Learning: A Comprehensive CSV-Based Classification Approach. Studies in Computational Intelligence. ISBN 978-96-8353-6 (eBook) doi.org/10.1007/978-96-8353-6
  30. LIFEx-texture: Tomoki Matsushita, Takayoshi Shinya, Toshihiko Nishisho, Koichi Sairyo, Yoshimi Bando, Hisanori Uehara, Masafumi Harada, The Diagnostic Ability of Texture Analysis in MR Imaging for Neurogenic Tumors, The Journal of Medical Investigation, 2025, Volume 72, Issue 3.4, Pages 367-374, Released on J-STAGE November 04, 2025, Online ISSN 1349-6867, Print ISSN 1343-1420, doi.org/10.2152/jmi.72.367
  31. LIFEx-texture: Ibis, K.; Durmaz, M.; Yanik, D.; Bunul, I.; Denizli, M.; Akyuz, E.; Khishigsuren, B.; Celik, A.I.; Kartal, M.G.D.; Kucucuk, N.S.; et al. Machine Learning-Based Prognostic Modelling Using MRI Radiomic Data in Cervical Cancer Treated with Definitive Chemoradiotherapy and Brachytherapy. Curr. Oncol. 2025, 32, 602. doi.org/10.3390/curroncol32110602
  32. LIFEx-texture: Aguirre-Meneses H, Stoehr-Muñoz P, Molina-Gonzalez M, et al. (October 24, 2025) Radiomics and the Image Biomarker Standardisation Initiative (IBSI): A Narrative Review Using a Six-Question Map and Implementation Framework for Reproducible Imaging Biomarkers. Cureus 17(10): e95335.  doi.org/10.7759/cureus.95335
  33. LIFEx-texture: Huang, Q., Mo, J., Deng, X. et al. NHOC/NHOP as novel biomarkers for predicting lymph node metastasis in NSCLC using PET/CT radiomics and machine learning: a two-center retrospective study. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07560-0
  34. LIFEx-texture: Sarioglu O, Canturk A, Yarol RC, Gulmez H, Sarioglu FC, Derebek E, et al. Machine learning using MR imaging radiomics can predict the response of large hepatocellular carcinoma to transarterial radioembolization. Niger J Clin Pract 2025;28:1111-20.  doi.org/10.4103/njcp.njcp_305_25
  35. LIFEx-texture: Yifei Deng. Advances in Immunotherapy of Biomarkers for Non-small Cell Lung Cancer Based on Radiomics. Transactions on Materials, Biotechnology and Life Sciences ISSN: 2960-1932, eISSN: 2960-2319 | Volume 8. MMTCS 2025 ( link )
  36. LIFEx-MTV: Lommen, M., Weindler, J.J., Jablonski, J. et al. Association between metabolic tumor burden and health-related quality of life in patients with classic Hodgkin lymphoma. Eur J Nucl Med Mol Imaging (2025). doi.org/10.1007/s00259-025-07569-5
  37. LIFEx-texture: Lanfranchi, F., Belgioia, L., Vita, D. et al. Baseline PSMA tumor volume as a prognostic marker in radical radiotherapy for prostate cancer: a propensity score-weighted retrospective analysis. Ann Nucl Med (2025).  doi.org/10.1007/s12149-025-02118-4
  38. LIFEx-texture: Lai, R., Tan, Q., Ding, C. et al. Habitat-based transformer model in pretreatment 18F-FDG PET imaging for predicting prognosis in cervical cancer: a two-center retrospective study. BMC Cancer 25, 1515 (2025).  doi.org/10.1186/s12885-025-14977-1
  39. LIFEx-texture: Andrianos, C.C.; Kostopoulos, S.A.; Kalatzis, I.K.; Glotsos, D.T.; Asvestas, P.A.; Cavouras, D.A.; Athanasiadis, E.I. Development of a Fully Optimized Convolutional Neural Network for Astrocytoma Classification in MRI Using Explainable Artificial Intelligence. J. Imaging 2025, 11, 343.  doi.org/10.3390/jimaging11100343
  40. LIFEx-texture: M Mureddu, F Fiz, G Morana, A Rossi, A Ramaglia, M L Garré, C Milanaccio, S Vella, A Piccardo, R Trò, M Fato, P10.20.A RADIOMICS-BASED GRADING OF PAEDIATRIC GLIOMAS USING [18F] F-DOPA PET/CT: INSIGHTS FROM THE PERITUMORAL BORDER, Neuro-Oncology, Volume 27, Issue Supplement_3, October 2025, Page iii100,  doi.org/10.1093/neuonc/noaf193.331
  41. LIFEx-texture: Kabanov, D.; Rubtsova, N.; Golbits, A.; Kaprin, A.; Sinitsyn, V.; Potievskiy, M. Radiomics-Based Preoperative Assessment of Muscle-Invasive Bladder Cancer Using Combined T2 and ADC MRI: A Multicohort Validation Study. J. Imaging 2025, 11, 342.  doi.org/10.3390/jimaging11100342
  42. LIFEx-MTV: Cui, C., Cao, J., Li, Y. et al. A proof of concept study of 18F-FDG PET/CT patient-level radiomics identify refractory/relapsed diffuse large B-cell lymphoma. Sci Rep 15, 33914 (2025). doi.org/10.1038/s41598-025-08223-8
  43. LIFEx-texture: Gholizade, M., Yazdani, E., Hosseini-Baharanchi, F.S. et al. Variations in radiomic features of the femoral head and neck during helical tomotherapy in prostate and rectal cancer patients. BMC Cancer 25, 1509 (2025).  doi.org/10.1186/s12885-025-14903-5
  44. LIFEx-MTV: Guo Yue-Honga, Tian Yingb, Huang Jing-Weia, Liu Ai-Junb, Yang Min-Fua. Prognostic value of tumor dissemination feature based on baseline 18F-FDG PET/CT in patients with newly diagnosed multiple myeloma. Nuclear Medicine Communications.  doi.org/10.1097/MNM.0000000000002059 , September 25, 2025
  45. LIFEx-texture: Sarioglu, O; Canturk, A; Yarol, RC; Gulmez, H; Sarioglu, FC; Derebek, E; Gulcu, A. Machine Learning using MR İmaging Radiomics can Predict the Response of Large Hepatocellular Carcinoma to Transarterial Radioembolization. Nigerian Journal of Clinical Practice 28(9):p 1111-1120, September 2025. doi.org/10.4103/njcp.njcp_305_25
  46. LIFEx-texture: Oliver Viering, Julia Brosch-Lenz, Ralph A. Bundschuh, Helen Scholtissek, Johanna S. Enke, Adriana Amerein, Georgine Wienand, Alexander Dierks, Malte Kircher, Marianne Patt, Christian H. Pfob, Constantin Lap. Biodistribution and Radiation Dosimetry of [68Ga]Ga-RAYZ-8009, a Glypican 3–Targeting Compound for Imaging of Hepatocellular Carcinoma. Journal of Nuclear Medicine Sep 2025, jnumed.125.270267; doi.org/10.2967/jnumed.125.270267
  47. LIFEx-texture: Thomas-Monier R, Lere-Chevaleyre A, Pereira B, Biau J, Bernadach M, Cassagnes L, Saroul N, Magnin B, Computed Tomography radiomic analysis of paraspinal muscles in the prognosis of advanced head and neck cancers, Clinical Nutrition ESPEN,  doi.org/10.1016/j.clnesp.2025.09.020
  48. LIFEx-texture: Yazdani E, Neizehbaz A, Karamzade-Ziarati N, et al. Transforming [177Lu]Lu-PSMA-617 treatment planning: Machine learning-based radiodosiomics and swin UNETR using pretherapy PSMA positron emission tomography/computed tomography (PET/CT). Med Phys. 2025; 52:e70030.  doi.org/10.1002/mp.70030
  49. LIFEx-MTV: Auriac J, Nioche C, Hovhannisyan-Baghdasarian N, et al. Comparison of organ volumes and standardized uptake values in [18F]FDG-PET/CT images using MOOSE and TotalSegmentator to segment CT images. Med Phys. 2025;52:e70025.  doi.org/10.1002/mp.70025
  50. LIFEx-texture: Talyshinskii, A., Ali, S., Gauhar, V. et al. CT-based radiomics for predicting stone-free rate after ESWL: a systematic review and meta-analysis. World J Urol 43, 566 (2025).  doi.org/10.1007/s00345-025-05933-6
  51. LIFEx-texture: Yu, C., Wang, J., Chen, L. et al. [18F]FDG PET/CT for outcome prediction in diffuse large B-cell lymphoma treated with polatuzumab vedotin-containing regimens. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07561-z
  52. LIFEx-texture: Lopci, E., Elia, C., De Re, V. et al. Predictive and prognostic role of volumetric analyses and lymphoma dissemination in pediatric HL: a prospective, multicenter, cohort study. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07537-z
  53. LIFEx-MTV: Yao, X., Wei, L., Wang, H. et al. Baseline [18F]FDG PET/CT characterization of extramedullary disease and prognostic value in relapsed/refractory B-cell acute lymphoblastic leukemia treated with CAR-T cells. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07562-y
  54. LIFEx-texture: Li S, Chen F, Wang L and Xiang Z (2025). Prediction of lymph node metastasis in lung adenocarcinoma using a PET/CT radiomics-based ensemble learning model and its pathological basis. Front. Oncol. 15:1618494.  doi.org/10.3389/fonc.2025.1618494
  55. LIFEx-texture: Francesco Bianconi, Muhammad Usama Khan, Hongbo Du, and Sabah Jassim. Experimental Assessment of Conventional Features, CNN-Based Features and Ensemble Schemes for Discriminating Benign Versus Malignant Lesions on Breast Ultrasound Images. SageJournals / Ultrasonic Imaging. First published online August 28, 2025. doi.org/10.1177/01617346251362168
  56. LIFEx-texture: Winkelmann, M., Raj, S.S., Jain, M.D. et al. Optimization and validation of the international metabolic prognostic index for CD19 CAR-T in large B-cell lymphoma. Blood Cancer J. 15, 144 (2025). doi.org/10.1038/s41408-025-01338-1
  57. LIFEx-texture: Koyluce, Nihat; Abdulrezzak, Ummuhan; Tutus, Ahmet. Volumetric 68 Ga- prostate-specific membrane antigen PET/computed tomography analysis of bone metastasis subtypes in prostate cancer: correlation with prostate-specific antigen and International Society of Urological Pathology grade. Nuclear Medicine Communications ():10.1097/MNM.0000000000002044, August 26, 2025.  doi.org/10.1097/MNM.0000000000002044
  58. LIFEx-texture: Gamberini, L., Astuti, G.M., Biavati, B. et al. Pulmonary contusion volume and radiomics as predictors of early-onset pneumonia in trauma patients, a retrospective single-centre study. Eur J Trauma Emerg Surg 51, 275 (2025). doi.org/10.1007/s00068-025-02952-1
  59. LIFEx-texture: Bishnoi, Komala; Agrawal, Kanhaiyalala; Parida, Girish Kumara; Majumdar, Saroj Kumar Dasb; Mishra, Pritinandac; Muduly, Dillip Kumard; Padhy, Biswa Mohane. Correlation of immunohistochemistry markers with textural characteristics derived from dual point F-18 fluorodeoxyglucose PET-CT in treatment naive locally advanced breast cancer patients. Nuclear Medicine Communications (): doi.org/10.1097/MNM.0000000000002042 , August 21, 2025
  60. LIFEx-texture: Zhang, Y., Li, J., Lü, L. et al. Evaluation of the efficacy of FDG-PET/CT in assessing the effects of BMMSC treatment in aged rhesus monkeys. Stem Cell Res Ther 16, 448 (2025).  doi.org/10.1186/s13287-025-04533-w
  61. LIFEx-texture: Dwivedi, P., Barage, S., Singh, R. et al. PET-based radiomic analysis in multicentre lung cancer study and impact of feature domain harmonization. Phys Eng Sci Med (2025).  doi.org/10.1007/s13246-025-01625-y
  62. LIFEx-texture: Zhang, Y., Li, J., Lü, L. et al. Evaluation of the efficacy of FDG-PET/CT in assessing the effects of BMMSC treatment in aged rhesus monkeys. Stem Cell Res Ther 16, 448 (2025).  doi.org/10.1186/s13287-025-04533-w
  63. LIFEx-texture: Beddok, A., Grogg, K., Nioche, C. et al. Predicting tumor recurrence site after reirradiation in head and neck cancer: a retrospective external validation of a published [18F]-FDG PET radiomic signature. Radiol med (2025).  doi.org/10.1007/s11547-025-02072-1
  64. LIFEx-texture: Zhang K, Wang G, Wang X, Kan Y, Wang W, Yang J. The baseline 18F-FDG PET/CT imaging features in pediatric patients with congenital neuroblastoma. BMC Med Imaging. 2025 Aug 14;25(1):330.  doi.org/10.1186/s12880-025-01863-2 . PMID: 40813959; PMCID: PMC12355819.
  65. LIFEx-texture: Hidenori Amaike, Masatoshi Kanda, Hirotsugu Yamazaki, Koki Nakamura, Li Ma, Ken Nagahata, Hiroyuki Nakamura, Arata Osanami, Naoya Yama, Masamitsu Hatakenaka, Masato Furuhashi, Hiroki Takahashi; The effectiveness of lesion detection for IgG4-related kidney diseases by diffusion-weighted imaging. Nephron 2025;  doi.org/10.1159/000547628
  66. LIFEx-texture: Ab Mumin, N., Liew, CH., Ong, SQ. et al. MRI-based texture analysis for breast cancer subtype classification in a multi-ethnic population. Magn Reson Mater Phy (2025).  doi.org/10.1007/s10334-025-01285-9
  67. LIFEx-main: Chunqiao Wu, Hongjie Hu, Fanger Bao, Zhiying Fei. Development of a multimodal predictive model using PET/CT radiomics and clinical data for preoperative assessment of lymphovascular invasion in gastric cancer. Am J Transl Res 2025;17(7):5441-5452 ajtr.org /ISSN:1943-8141/AJTR0163464  e-century.us/files/ajtr/17/7/ajtr0163464.pdf
  68. LIFEx-texture: Seify, N., Khezerloo, D., Jahanshahi, A. et al. Longitudinal assessment of MRI-based radiomics feature changes in caudate and putamen over progression of parkinson’s disease. Egypt J Radiol Nucl Med 56, 135 (2025).  doi.org/10.1186/s43055-025-01552-8
  69. LIFEx-MTV: Zhang, H., Li, C., Chen, Y. et al. Vasculature cast sign on 18F-FDG PET/CT: a specific imaging marker for pediatric T-lymphoblastic lymphoma. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07488-5
  70. LIFEx-MTV: Kargar Samani I, Gheysens O, Regnier M, Collard A, André M, Van Den Neste E and Vander Borght T (2025) Prognostic value of a simple distance index derived from PET maximum intensity projection. Front. Med. 12:1565525.  doi.org/10.3389/fmed.2025.1565525
  71. LIFEx-texture: Tang W, Chen H, Liu P, Zhang Y. Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer. Front Oncol. 2025 Jun 25;15:1620217.  doi.org/10.3389/fonc.2025.1620217 PMID: 40636691; PMCID: PMC12237632.
  72. LIFEx-texture: Serçe Unat D, Aguloğlu N, Unat ÖS, Aksu A, Erer OF, Özdemir Ö, Polat G. Non-invasive procedure in differential diagnosis of sarcoidosis and tuberculosis lymph nodes: Radiomic model of 18F-FDG PET-CT. Sarcoidosis Vasc Diffuse Lung Dis. 2025;42(2):16188.  doi.org/10.36141/svdld.v42i2.16188 Epub 2025 Jun 25. PMCID: PMC12242878.
  73. LIFEx-texture: A Italiano, O Gautier, J Dupont, T Assi, L Dawi, L Lawrance, A Bone, G Jardali, A Choucair, S Ammari, A Bayle, E Rouleau, PH Cournede, I Borget, B Besse, F Barlesi, C Massard, N Lassau. The correlation of liquid biopsy genomic data to radiomics in colon, pancreatic, lung and prostatic cancer patients. European Journal of Cancer, Volume 226, 2025, 115609, ISSN 0959-8049, doi.org/10.1016/j.ejca.2025.115609
  74. LIFEx-mtv: Dondolin, R., Garrou, F., Almasri, M. et al. Integration of [18F]FDG-PET radiomics with liquid biopsy improves outcome prediction in newly diagnosed diffuse large B-cell lymphoma. Leukemia (2025).  doi.org/10.1038/s41375-025-02688-2
  75. LIFEx-texture: M El-Jammal, C Chung. Paving a Path to Clinical Impact with Radiomics: Enabling Reproducibility and Reach. Cancer Res (2025) 85 (13): 2353–2355. doi.org/10.1158/0008-5472.CAN-25-2083
  76. LIFEx-main: B Delache, AR Garnier, C Herate, F Relouzat, P Lê-Bury, J Lemaitre, A Berriche, Q Sconosciuti, E Navarre, N Verguet, J Creppy, O Gorgé, JN Tournier, F Ducancel, L Vecellio, R Le Grand, T Naninck. Positron emission tomography-based comparison of methods for exposing macaques to respiratory pathogens, Journal of Aerosol Science, 2025, 106646, ISSN 0021-8502, doi.org/10.1016/j.jaerosci.2025.106646
  77. LIFEx-main: Kim, JY., Lee, C., Lee, JH. et al. Comparison of the maximum standardized uptake value and magnetic resonance imaging characteristics between temporomandibular joint osteoarthrosis and osteoarthritis. Sci Rep 15, 23542 (2025).  doi.org/10.1038/s41598-025-06045-2
  78. LIFEx-texture: Valibeiglou, Z., Islamian, J.P., Soleymani, Y. et al. Enhancing radiomics robustness using bayesian penalized likelihood PET reconstruction: application to Phantom and non-small cell lung cancer patient studies. BMC Med Imaging 25, 223 (2025).  doi.org/10.1186/s12880-025-01774-2
  79. LIFEx-MTV: Samani I, Gheysens O, Regnier M, Collard A, André M, Van Den Neste E, Vander Borght T. Prognostic value of a simple distance index derived from PET maximum intensity projection. Front. Med.Sec. Nuclear Medicine. Volume 12 - 2025,  doi.org/10.3389/fmed.2025.1565525
  80. LIFEx-Main: Zhou X, Yin K, Hong H, Yi H, Li L. Combined Predictive Value of GLIM-Defined Malnutrition and Preoperative Adipose Tissue 18F-FDG Uptake for Recurrence-Free Survival After Radical Gastrectomy in Patients with Gastric Cancer. Current Oncology. 2025; 32(6):363. doi.org/10.3390/curroncol32060363
  81. LIFEx-texture: Ge, F., Wu, T., Yang, X. et al. Feasibility analysis of metabolic parameters based on baseline 18F-FDG PET/CT to predict heterogeneity and recurrence of diffuse large B-cell lymphoma. Ann Hematol (2025). doi.org/10.1007/s00277-025-06409-8
  82. LIFEx-texture: Fasmer, K.E., Gulati, A., Lindås, S. et al. Predicting aggressive disease and poor outcome in endometrial cancer using preoperative [18F]FDG PET primary tumor radiomics. Eur J Nucl Med Mol Imaging (2025). doi.org/10.1007/s00259-025-07335-7
  83. LIFEx-texture: Kotaro Ito, Ryoga Atsumi, Hirotaka Muraoka, Satoshi Tokunaga, Yuta Kohinata, Tomohiro Komatsu, Takashi Kaneda. Quantitative Assessment of the Parotid Gland Using Computed Tomography Texture Analysis to Detect Patients With Dyslipidemia. Volume22, Issue3, September 2025, e70011,  doi.org/10.1002/osi2.70011
  84. LIFEx-MTV: Guo, W., Jiang, H., Wang, C. et al. Predictive value of [18F]FDG PET-derived parameters for microsatellite instability and prognosis in patients with colorectal cancer. Eur Radiol (2025). doi.org/10.1007/s00330-025-11732-9
  85. LIFEx-dynPET: Hui Yuan, Fanghu Wang, Yang Chen, Xiaoqiang Pan, Qing Zhang, Tao Sun, Lei Jiang. Kinetic Modeling and Parametric Imaging of 13N-NH3 in Treatment-Naïve Lung Cancer. Published June 13, 2025. Mol. Pharmaceutics 2025, XXXX, XXX, XXX-XXX  doi.org/10.1021/acs.molpharmaceut.5c00602
  86. LIFEx-texture: Zhigang Chen, Huiying Lu, Ao Liu, Jia Weng, Lei Gan, Lina Zhou, Xiao Ding and Shicheng Li. TRANS: a prediction model for EGFR mutation status in NSCLC based on radiomics and clinical features. Respiratory Research (2025) 26:211  doi.org/10.1186/s12931-025-03287-6
  87. LIFEx-Texture: Salvatore Pezzino, Tonia Luca, Mariacarla Castorina, Stefano Puleo and Sergio Castorina. Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy. 2025 Prog. Biomed. Eng. 7 032002 doi.org/10.1088/2516-1091/adc85e
  88. LIFEx-Texture: Eva Jambon, Camille Courtine, Bruno Soulabaille, David Chéchin, Benjamin Robert, Joffrey Sarrazin,  Gaëlle Margue, Jean-Christophe Bernhard, Yann Le Bras, Amandine Crombé. Improving the Accuracy and Repeatability of Renal Stiffness Measurement With Magnetic Resonance Elastography: Influence of Vibration Frequency, Acquisition Orientation, and Postprocessing - A Phantom and Volunteer Study. NMR in Biomedicine, 2025; 38:e70054 doi.org/10.1002/nbm.70054
  89. LIFEx-MTV: Rexhep Durmo, Benedetta Donati, Louis Rebaud, Anne Segolene Cottereau, Alessia Ruffini, Maria Elena Nizzoli, Sabino Ciavarella, Maria Carmela Vegliante, Christophe Nioche, Michel Meignan, Francesco Merli, Annibale Versari, Alessia Ciarrocchi, Irene Buvat, Stefano Luminari. Prognostic value of lesion dissemination in doxorubicin, bleomycin, vinblastine, and dacarbazine‐treated, interimPET‐negative classical Hodgkin Lymphoma patients: A radio‐genomic study. Hematological Oncology. 2022;40:645–657. doi.org/10.1002/hon.3025
  90. LIFEx-Texture: Pellegrino, S.; Panico, M.; Bologna, R.; Morra, R.; Servetto, A.; Bianco, R.; Del Vecchio, S.; Fonti, R. Texture Analysis of 68Ga-DOTATOC PET/CT Images for the Prediction of Outcome in Patients with Neuroendocrine Tumors. Biomedicines 2025, 13, 1286. doi.org/10.3390/biomedicines13061286
  91. LIFEx-Texture: Kartal, A.S., Kartal, M.O., Gülleroğlu, N.B. et al. Texture analysis and metabolic parameters of 18F-FDG PET/CT to predict primary tumour response and prognosis of paediatric soft tissue sarcomas. Eur J Nucl Med Mol Imaging (2025). doi.org/10.1007/s00259-025-07359-z
  92. LIFEx-Texture: Lian A, Ketcherside T, Liu A, Han C, Al Feghali KA, Maniyedath A, Amini A, Ladbury C. Evaluation of the stability of radiomic features of non-irradiated organs utilizing fan-beam kilovoltage computed tomography. Med Phys. 2025 May 29. https: doi.org/10.1002/mp.17914 . Epub ahead of print. PMID: 40438900.
  93. LIFEx-texture: Salvatore Pezzino et al 2025. Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy. Prog. Biomed. Eng. 7 032002. doi.org/10.1088/2516-1091/adc85e
  94. LIFEx-texture: Andres A. Kohan, S.A. Mirshahvalad, R. Hinzpeter, R. Kulanthaivelu, L. Avery, C. Ortega, U. Metser, A. Hope, P. Veit-Haibach. External Validation of a CT-Based Radiogenomics Model for the Detection of EGFR Mutation in NSCLC and the Impact of Prevalence in Model Building by Using Synthetic Minority Over Sampling (SMOTE): Lessons Learned, Academic Radiology, 2025, ISSN 1076-6332, doi.org/10.1016/j.acra.2025.04.064
  95. LIFEx-MTV: Zheng, C., Miao, J., Xu, L. et al. Novel PET imaging biomarkers as predictors of postoperative recurrence in lung adenocarcinoma. BMC Cancer 25, 874 (2025).  doi.org/10.1186/s12885-025-14263-0
  96. LIFEx-texture: Kim, M., Gu, W., Iwakawa, R.K. et al. Integrative Analysis of 18F-FDG PET Radiomics and mRNA Expression in Recurrent/Metastatic Oral Squamous Cell Carcinoma: A Cross-Sectional Study. Mol Imaging Biol (2025). doi.org/10.1007/s11307-025-02012-5
  97. LIFEx-texture-MTV: Kleiburg, F., Geus-Oei, L. F. de, Spijkerman, R., Noortman, W. A., Velden, F. H. P. van, Manohar, S., … Heijmen, L. (2025). Baseline PSMA PET/CT parameters predict overall survival and treatment response in metastatic castration-resistant prostate cancer patients. European Radiology.  doi.org/10.1007/s00330-025-11360-3
  98. LIFEx-texture: Chen, L., Wang, J., Jin, C. et al. Initial [18F]FDG PET/CT study for survival evaluation of lung transplantation patients with interstitial lung disease. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07315-x
  99. LIFEx-MTV: Yao, X., Wang, H., Lei, X. et al. 18F-FDG PET/CT for predicting prognosis of B-cell non-Hodgkin lymphoma patients treated with chimeric antigen receptor T cells: the value of pre-infusion and M1 image. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07302-2
  100. LIFEx-texture: Shin H-B,  Sheen H,  Oh J-H,  Choi YE,  Sung K,  Kim HJ.  Evaluating feature extraction reproducibility across image biomarker standardization initiative-compliant radiomics platforms using a digital phantom. J Appl Clin Med Phys.  2025;e70110. doi.org/10.1002/acm2.70110
  101. LIFEx-texture: Xu L, Chen Z, Zhu D, Wang Y. The Application Status of Radiomics-Based Machine Learning in Intrahepatic Cholangiocarcinoma: Systematic Review and Meta-Analysis. J Med Internet Res 2025;27:e69906. doi.org/10.2196/69906 PMID: 40323647
  102. LIFEx-texture: Cvachovec, P., Bicu, A.S., Schmidt, R. et al. Longitudinal stability of HyperSightTM-CBCT based radiomic features in patients with CT guided adaptive SBRT for prostate cancer.Sci Rep 15, 15863 (2025).  doi.org/10.1038/s41598-025-99920-x
  103. LIFEx-MTV: Zelda Paquier; Jennifer Dhont; Thomas Guiot; Rita Saude Conde; Francesco Sclafani; Alain Hendlisz. Development and Validation of an 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography–Based Imaging Score to Predict 12-Week Life Expectancy in Advanced Chemorefractory Colorectal Cancer. JCO Clin Cancer Inform 9:e2400207.  doi.org/10.1200/CCI-24-00207
  104. LIFEx-texture: Adarve-Castro, A., Soria-Utrilla, V., Castro-García, J.M. et al. Advanced radiomic prediction of osteoporosis in primary hyperparathyroidism: a machine learning-based analysis of CT images. Radiol med (2025).  doi.org/10.1007/s11547-025-02004-z
  105. LIFEx-texture: Peng, Y., Shi, M., Xiong, D. et al. Preoperative assessment and prognostic prediction of gastric cancer patients with peritoneal metastasis using 18F-FDG PET/CT before conversion surgery. EJNMMI Res 15, 46 (2025).  doi.org/10.1186/s13550-025-01244-4
  106. LIFEx-texture: Gemmell, A.J., Brown, C.M., Ray, S. et al. Robustness of textural analysis features in quantitative 99 mTc and 177Lu SPECT-CT phantom acquisitions. EJNMMI Phys 12, 40 (2025).  doi.org/10.1186/s40658-025-00749-0
  107. LIFEx-Texture: Bilgin E, Bilgin EY, Bayrak A, Torenek S. Advanced Radiomics for Predicting Extracapsular Invasion of Metastatic Axillary Lymph Nodes in Breast Cancer Patients Using CT Imaging. J Coll Physicians Surg Pak 2025; 35(04):415-419  doi.org/10.29271/jcpsp.2025.04.415
  108. LIFEx-main: Stien, G., Zinsz, A., Ahrari, S. et al. PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): methodological application in [18F]-FDOPA PET imaging.EJNMMI Res 15, 44 (2025).  doi.org/10.1186/s13550-025-01239-1  
  109. LIFEx-texture: Yali Cui, Yao Li, Wenhao Hu, Zhifang Wu, Sijin Li, Hongliang Wang. Evaluating ΔMTV%, ΔDmax%, and %ΔSUVmax of 18F-FDG PET/CT for mid-treatment efficacy and prognosis in diffuse large B-cell lymphoma. Discover Oncology; New York Vol. 16, Iss. 1,  (Dec 2025): 411. doi.org/10.1007/s12672-025-02126-w
  110. LIFEx-texture: Melek YAKAR, Durmus ETIZ, Eyyup GULBANDILAR, Kerem DURUER, Ergin ERDEN. Radiomic-Assistant Response Prediction to Stereotactic Body Radiotherapy in Early Stage Lung Cancer. UHOD Number: 1 Volume: 35 Year: 2025.  doi.org/10.4999/uhod.257762
  111. LIFEx-texture: Zhao, J., Zhao, W., Chen, M. et al. 18F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study. J Cancer Res Clin Oncol 151, 125 (2025).  doi.org/10.1007/s00432-025-06172-3
  112. LIFEx-texture: Cui, Y., Li, Y., Hu, W. et al. Evaluating ΔMTV%, ΔDmax%, and %ΔSUVmax of 18F-FDG PET/CT for mid-treatment efficacy and prognosis in diffuse large B-cell lymphoma. Discov Onc 16, 411 (2025). doi.org/10.1007/s12672-025-02126-w
  113. LIFEx-texture: Takeharu Kiso, Yukinori Okada, Satoru Kawata, Kouta Shichiji, Eiichiro Okumura, Noritaka Hatsumi, Ryohei Matsuura, Masaki Kaminaga, Hikaru Kuwano, Erika Okumura. Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value. European Journal of Radiology Open, Volume 14, 2025, 100649, ISSN 2352-0477,  doi.org/10.1016/j.ejro.2025.100649
  114. LIFEx-main: Yexin Su, Hongyue Zhao, Zhehao Lyu, Peng Xu, Ziyue Zhang, Huiting Zhang, Mengjiao Wang, Lin Tian, Peng Fu. Quantification of Intratumoral Heterogeneity Based on Habitat Analysis for Preoperative Assessment of Lymphovascular Invasion in Colorectal Cancer. Academic Radiology, 2025, ISSN 1076-6332,  doi.org/10.1016/j.acra.2025.03.014
  115. LIFEx-texture: Mengye Peng, Menglu Wang, Xinyue Yang, Yanmei Wang, Lizhi Xie, Wenxin An, Fan Ge, Chen Yang, Kezheng Wang. Prediction of PD-L1 Expression in NSCLC patients Using PET/CT Radiomics and Prognostic Modeling for Immunotherapy in PD-L1-Positive NSCLC Patients. Clinical Radiology. 2025. 106915, ISSN 0009-9260,  doi.org/10.1016/j.crad.2025.106915
  116. LIFEx-MTV: Hu, J., Cheng, R., Quan, M. et al. Hypermetabolic pulmonary lesions detection and diagnosis based on PET/CT imaging and deep learning models. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07215-0
  117. LIFEx-texture: Liao Z, Luo D, Tang X, Huang F, Zhang X. MRI-based radiomics for predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review and meta-analysis. Front Oncol. 2025 Mar 10;15:1550838.  doi.org/10.3389/fonc.2025.1550838 PMID: 40129922; PMCID: PMC11930822.
  118. LIFEx-main: Shrestha et al., (2025). RT-utils: A Minimal Python Library for RT-struct Manipulation. Journal of Open Source Software, 10(107), 7361,  doi.org/10.21105/joss.07361
  119. LIFEx-texture: Isemoto, K., Waseda, Y., Fujiwara, M., Kimura, K., Hirahara, D., Saho, T., Takaya, E., Arita, Y., Kwee, T. C., Fukuda, S., Tanaka, H., Yoshida, S., & Fujii, Y. (2025). Predictive Potential of Contrast-Enhanced MRI-Based Delta-Radiomics for Chemoradiation Responsiveness in Muscle-Invasive Bladder Cancer. Diagnostics, 15(7), 801.  doi.org/10.3390/diagnostics15070801
  120. LIFEx-texture: Esat Kaba, Hande Melike Bülbül, Mehmet Kıvrak, Nur Hürsoy. Multisequence combined magnetic resonance imaging radiomics model to noninvasively predict nuclear grade of clear cell renal cell carcinoma: interpretable model development. Rev Assoc Med Bras. 2025;71(1):e20241012.  doi.org/10.1590/1806-9282.20241012
  121. LIFEx-texture: J. Wang, W. Tang, J. Zhu, J. Cui, Y. Chen, M. Gu, H. Xu, M. Zhan, Q. Chen, B. Xu. Predicting the pathological subdiagnosis of benign prostatic hyperplasia with MRI radiomics: A noninvasive approach. VIEW. 2025, 20240092. doi.org/10.1002/VIW.20240092
  122. LIFEx-texture: Magnin Cheryl Y., Lauer David, Ammeter Michael, Gote-Schniering Janine. From images to clinical insights: an educational review on radiomics in lung diseases. 21:1, 230225. doi.org/10.1183/20734735.0225-2023
  123. LIFEx-texture:  Sriramganesh Gokavarapu, K Venkata Rao, Gorla Srinivas, Dasari Siva Krishna, Enhancing Lung Cancer Detection: Optimizing Deep Learning with Convolutional Block Attention Module, Journal of Artificial Intelligence and Technology (2025), DOI: doi.org/10.37965/jait.2025.0668
  124. LIFEx-texture: Liu, H., Meng, X., Wang, G. et al. Differentiating second primary lung cancer from pulmonary metastasis in patients of single solitary pulmonary lesion with extrapulmonary tumor using multiparametric analysis of FDG PET/CT. Ann Nucl Med(2025).  doi.org/10.1007/s12149-025-02034-7
  125. LIFEx-texture: Alireza Safarian, Seyed Ali Mirshahvalad, Hadi Nasrollahi, Theresa Jung, Christian Pirich, Hossein Arabi, Mohsen Beheshti. Impact of [18F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role, Seminars in Nuclear Medicine, 2025, ISSN 0001-2998,  doi.org/10.1053/j.semnuclmed.2025.02.006
  126. LIFEx-texture: Liu, H., Meng, X., Wang, G. et al. Differentiating second primary lung cancer from pulmonary metastasis in patients of single solitary pulmonary lesion with extrapulmonary tumor using multiparametric analysis of FDG PET/CT. Ann Nucl Med(2025).  doi.org/10.1007/s12149-025-02034-7
  127. LIFEx-texture: Tan Qianqian, Teng Yue, Sun Yiwen, Xu Pei, Xu Yiduo, Chen Qiaoliang, He Jian, Lai Ruihe. Prognostic value of 18F-FDG PET/CT metabolic parameters TMTV in patients with stage Ⅳ endometrial cancer[J]. Int J Radiat Med Nucl Med.  doi.org/10.3760/cma.j.cn121381-202403022-00506
  128. LIFEx-texture: Lazaros K, Adam S, Krokidis MG, Exarchos T, Vlamos P, Vrahatis AG. Non-Invasive Biomarkers in the Era of Big Data and Machine Learning. Sensors. 2025; 25(5):1396. doi.org/10.3390/s25051396
  129. LIFEx-texture: Yang, Mao et al. Multimodal integration of liquid biopsy and radiology for the noninvasive diagnosis of gallbladder cancer and benign disorders. Cancer Cell, Volume 43, Issue 3, 398 - 412.e4.  www.cell.com/cancer-cell/fulltext/S1535-6108(25)00063-7
  130. LIFEx-texture: Lazaros K, Adam S, Krokidis MG, Exarchos T, Vlamos P, Vrahatis AG. Non-Invasive Biomarkers in the Era of Big Data and Machine Learning. Sensors. 2025; 25(5):1396. doi.org/10.3390/s25051396
  131. LIFEx-texture: Peng, M., Wang, M., An, W. et al. Predictive classification of lung cancer pathological based on PET/CT radiomics. Jpn J Radiol (2025). doi.org/10.1007/s11604-025-01742-4
  132. LIFEx-texture: Gennaro, N.; Soliman, M.; Borhani, A.A.; Kelahan, L.; Savas, H.; Avery, R.; Subedi, K.; Trabzonlu, T.A.; Krumpelman, C.; Yaghmai, V.; et al. Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer. Tomography 2025, 11, 20. doi.org/10.3390/tomography11030020
  133. LIFEx-Main: Ronga MG, Gesualdi F, Bonfrate A, et al. Comparison of secondary radiation dose between pencil beam scanning and scattered delivery for proton and VHEE radiotherapy. Med Phys. 2025;1-10.  doi.org/10.1002/mp.17700
  134. Zhang, Yichi and Xue, Le and Zhang, Wenbo and Li, Lanlan and Liu, Yuchen and Jiang, Chen and Cheng, Yuan and Qi, Yuan. SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images.  arxiv.org/pdf/2502.14351
  135. LIFEx-MTV: Albano, D., Temponi, A., Bertagna, F. et al. The prognostic role of staging [18F]PSMA-1007 PET/CT volumetric and dissemination features in prostate cancer. Ann Nucl Med (2025).  doi.org/10.1007/s12149-025-02026-7
  136. LIFEx-main: Liu, Y., Wang, J., Du, B. et al. Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point 18F-FDG PET/CT. Cancer Imaging 25, 17 (2025).  doi.org/10.1186/s40644-025-00834-8
  137. LIFEx-texture: Pellegrino S, Fonti R, Morra R, Di Donna E, Servetto A, Bianco R, Del Vecchio S. Prognostic Value of Tumor Dissemination (Dmax) Derived from Basal 18F-FDG Positron Emission Tomography/Computed Tomography in Patients with Advanced Non-Small-Cell Lung Cancer. Biomedicines. 2025; 13(2):477.  www.mdpi.com/2227-9059/13/2/477
  138. LIFEx-texture: Dwivedi P, Sagar S, AK Jha, S Choudhury, Venkatesh R. Robustness of 18F-FDG PET Radiomic Features in Lung Cancer: Impact of Advanced Reconstruction Algorithm.  J. Nucl. Med. Technol. 2025/02/05. doi.org/10.2967/jnmt.124.268252
  139. LIFEx-texture: Filippi, L., Bianconi, F., Minestrini, M. et al. Multi-centre data harmonisation applied to heart-to-mediastinum quantification in parkinsonism (ITA-MIBG): a cross-calibration phantom study with tube and bottle. Clin Transl Imaging (2025).  doi.org/10.1007/s40336-025-00681-4
  140. LIFEx-texture: Jiang, C., Jiang, Z., Zhang, Z. et al. An explainable transformer model integrating PET and tabular data for histologic grading and prognosis of follicular lymphoma: a multi-institutional digital biopsy study. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-025-07090-9
  141. LIFEx-texture: Beaumont H, Iannessi A, Thinnes A, Jacques S, Quintás-Cardama A. Radiomics-Based Prediction of Treatment Response to TRuC-T Cell Therapy in Patients with Mesothelioma: A Pilot Study. Cancers. 2025; 17(3):463. doi.org/10.3390/cancers17030463
  142. LIFEx-texture: Jiang, C., Qian, C., Jiang, Q. et al. Virtual biopsy for non-invasive identification of follicular lymphoma histologic transformation using radiomics-based imaging biomarker from PET/CT. BMC Med 23, 49 (2025).  doi.org/10.1186/s12916-025-03893-7
  143. LIFEx-MTV: Wen, Z., Gao, X., Wu, Q. et al. Baseline [18F]FDG PET/CT radiomics for predicting interim efficacy in follicular lymphoma treated with first-line R-CHOP. BMC Cancer 25, 128 (2025).  doi.org/10.1186/s12885-025-13507-3
  144. LIFEx-MTV-texture: Kleiburg, F., de Geus-Oei, LF., Spijkerman, R. et al. Baseline PSMA PET/CT parameters predict overall survival and treatment response in metastatic castration-resistant prostate cancer patients. Eur Radiol (2025).  doi.org/10.1007/s00330-025-11360-3
  145. LIFEx-texture: Qi, L., Li, X., Ni, J. et al. Construction of feature selection and efficacy prediction model for transformation therapy of locally advanced pancreatic cancer based on CT, 18F-FDG PET/CT, DNA mutation, and CA199. Cancer Cell Int 25, 19 (2025).  doi.org/10.1186/s12935-025-03639-8
  146. LIFEx-texture: Ahrari, S., Zaragori, T., Zinsz, A. et al. Clinical impact of an explainable machine learning with amino acid PET imaging: application to the diagnosis of aggressive glioma. Eur J Nucl Med Mol Imaging (2025).  doi.org/10.1007/s00259-024-07053-6
  147. LIFEx-texture: Captier, N., Lerousseau, M., Orlhac, F. et al. Integration of clinical, pathological, radiological, and transcriptomic data improves prediction for first-line immunotherapy outcome in metastatic non-small cell lung cancer. Nat Commun 16, 614 (2025).  doi.org/10.1038/s41467-025-55847-5
  148. LIFEx-texture: Zhou Y, Zhou XY, Xu YC, Ma XL, Tian R. Radiomics based on 18 F-FDG PET for predicting treatment response and prognosis in newly diagnosed diffuse large B-cell lymphoma patients: do lesion selection and segmentation methods matter? Quant Imaging Med Surg 2025;15(1):103-120.  doi.org/10.21037/qims-24-585
  149. LIFEx-texture: Bei-Hui Xue, Shuang-Li Chen, Jun-Ping Lan, Li-Li Wang, Jia-Geng Xie, Xiang-wu Zheng, Liang-Xing Wang, Kun Tang. Explainable PET-Based Habitat and Peritumoral Machine Learning Model for Predicting Progression-free Survival in Clinical Stage IA Pure-Solid Non-small Cell Lung Cancer: A Two-center Study, Academic Radiology, 2025, ISSN 1076-6332. doi.org/10.1016/j.acra.2024.12.038

Please Log in or Create an account to join the conversation.

Time to create page: 0.829 seconds