Radiomics in Medical Imaging Analysis

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Guha, S., Ibrahim, A., Geng, P., Wu, Q., Chou, Y., Akin, O., Schwartz, L. H., Xie, C.-M., & Zhao, B. (2025). Variability of HCC Tumor Diameter and Density Measurements on Dynamic Contrast-Enhanced Computed Tomography. Tomography, 11(3), 36. https://doi.org/10.3390/tomography11030036
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Zhao, B., Obuchowski, N., Yang, H., Chou, Y., Ma, H., Guo, P., Tang, Y., Schwartz, L., & Sullivan, D. (2025). Comparing quantitative imaging biomarker alliance volumetric CT classifications with RECIST response categories. Radiology Advances, 2(1). https://doi.org/10.1093/radadv/umaf001
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Adamo, R. G., Lam, E., Salameh, J.-P., van der Pol, C. B., Goins, S. M., Dawit, H., Costa, A. F., Levis, B., Singal, A. G., Chernyak, V., Sirlin, C. B., Bashir, M. R., Tang, A., Alhasan, A., Allen, B. C., Reiner, C. S., Clarke, C., Ludwig, D. R., Cerny, M., … McInnes, M. D. F. (2024). Do Risk Factors for HCC Impact the Association of CT/MRI LIRADS Major Features With HCC? An Individual Participant Data Meta-Analysis. Canadian Association of Radiologists Journal. https://doi.org/10.1177/08465371241306297
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Dierksen, F., Sommer, J. K., Tran, A. T., Lin, H., Haider, S. P., Maier, I. L., Aneja, S., Sanelli, P. C., Malhotra, A., Qureshi, A. I., Claassen, J., Park, S., Murthy, S. B., Falcone, G. J., Sheth, K. N., & Payabvash, S. (2024). Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT). Diagnostics, 14(24), 2827. https://doi.org/10.3390/diagnostics14242827
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Alshikho, M. J., Morales, C., Pyne, J. D., Amarante, E., Lao, P. J., Turney, I. C., Edwards, N. C., Gu, Y., Manly, J. J., Mayeux, R., & Brickman, A. M. (2024). Characterizing White Matter Hyperintensity (WMH) Patterns with Texture‐Based Analysis. Alzheimer’s & Dementia, 20(S2). Portico. https://doi.org/10.1002/alz.091712
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Gunasekaran, T. I., Lee, A. J., Lao, P. J., Gutierrez, J., Manly, J. J., Gu, Y., Brickman, A. M., Honig, L. S., Vardarajan, B. N., & Mayeux, R. (2024). Understanding Biomarker Discordance: MRI and PET Phenotypes Shed Light on Alzheimer’s Pathology. Alzheimer’s & Dementia, 20(S8). Portico. https://doi.org/10.1002/alz.095708
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Bartsch, S. J., Brožová, K., Fürböck, C., Friske, J., Laimer-Gruber, D., Helbich, T. H., Hacker, M., Kuntner, C., Kratochwill, K., Kenner, L., Langs, G., Pinker, K., & Wanek, T. (2024). Methodological aspects of correlative, multimodal, multiparametric breast cancer imaging: from data acquisition to image processing for AI-based radioproteomics in a preclinical setting. Frontiers in Biomaterials Science, 3. https://doi.org/10.3389/fbiom.2024.1420114
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Wang, H., Argenziano, M. G., Yoon, H., Boyett, D., Save, A., Petridis, P., Savage, W., Jackson, P., Hawkins-Daarud, A., Tran, N., Hu, L., Singleton, K. W., Paulson, L., Dalahmah, O. A., Bruce, J. N., Grinband, J., Swanson, K. R., Canoll, P., & Li, J. (2024). Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma. Npj Digital Medicine, 7(1). https://doi.org/10.1038/s41746-024-01277-4
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Ibrahim, A., Guha, S., Lu, L., Geng, P., Wu, Q., Chou, Y., Yang, H., Wang, D., Schwartz, L. H., Xie, C., & Zhao, B. (2024). The reproducibility and predictivity of radiomic features extracted from dynamic contrast-enhanced computed tomography of hepatocellular carcinoma. PLOS ONE, 19(9), e0310486. https://doi.org/10.1371/journal.pone.0310486
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Shuryak, I., Wang, E., & Brenner, D. J. (2024). Understanding the impact of radiotherapy fractionation on overall survival in a large head and neck squamous cell carcinoma dataset: a comprehensive approach combining mechanistic and machine learning models. Frontiers in Oncology, 14. https://doi.org/10.3389/fonc.2024.1422211
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Ma, J., Yoon, J. H., Lu, L., Yang, H., Guo, P., Yang, D., Li, J., Shen, J., Schwartz, L. H., & Zhao, B. (2024). A quantitative analysis of the improvement provided by comprehensive annotation on CT lesion detection using deep learning. Journal of Applied Clinical Medical Physics. Portico. https://doi.org/10.1002/acm2.14434
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Saqi, A., Liu, Y., Politis, M. G., Salvatore, M., & Jambawalikar, S. (2024). Combined expert-in-the-loop—random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments. Journal of Translational Medicine, 22(1). https://doi.org/10.1186/s12967-024-05394-2
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Resch, D., Lo Gullo, R., Teuwen, J., Semturs, F., Hummel, J., Resch, A., & Pinker, K. (2024). AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance. Radiology: Imaging Cancer, 6(4). https://doi.org/10.1148/rycan.230149
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McGuinness, J. E., Anderson, G. L., Mutasa, S., Hershman, D. L., Terry, M. B., Tehranifar, P., Lew, D. L., Yee, M., Brown, E. A., Kairouz, S. S., Kuwajerwala, N., Bevers, T. B., Doster, J. E., Zarwan, C., Kruper, L., Minasian, L. M., Ford, L., Arun, B., Neuhouser, M. L., … Crew, K. D. (2024). Effects of vitamin D supplementation on a deep learning–based mammographic evaluation in SWOG S0812. JNCI Cancer Spectrum, 8(4). https://doi.org/10.1093/jncics/pkae042
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Wang, L., Wang, H., D’Angelo, F., Curtin, L., Sereduk, C. P., Leon, G. D., Singleton, K. W., Urcuyo, J., Hawkins-Daarud, A., Jackson, P. R., Krishna, C., Zimmerman, R. S., Patra, D. P., Bendok, B. R., Smith, K. A., Nakaji, P., Donev, K., Baxter, L. C., Mrugała, M. M., … Li, J. (2024). Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. PLOS ONE, 19(4), e0299267. https://doi.org/10.1371/journal.pone.0299267
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Columbia Affiliation
Guha, S., Ibrahim, A., Wu, Q., Geng, P., Chou, Y., Yang, H., Ma, J., Lu, L., Wang, D., Schwartz, L. H., Xie, C., & Zhao, B. (2024). Machine learning-based identification of contrast-enhancement phase of computed tomography scans. PLOS ONE, 19(2), e0294581. https://doi.org/10.1371/journal.pone.0294581
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Duffau, H., Berger, M., Brastianos, P. K., Sanai, N., Mandonnet, E., & McKhann, G. M. (2024). Introduction: Contemporary management of low-grade gliomas: from tumor biology to the patient’s quality of life. Neurosurgical Focus, 56(2), E1. https://doi.org/10.3171/2023.11.focus23731
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Rayn, K., Gupta, V., Mulinti, S., Clark, R., Magliari, A., Chaudhari, S., Garima, G., & Beriwal, S. (2024). Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers. Journal of Cancer Research and Therapeutics, 20(3), 1020–1025. https://doi.org/10.4103/jcrt.jcrt_769_23
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Liu, Y., Hsu, H. Y., Lin, T., Peng, B., Saqi, A., Salvatore, M. M., & Jambawalikar, S. (2024). Lung nodule malignancy classification with associated pulmonary fibrosis using 3D attention-gated convolutional network with CT scans. Journal of Translational Medicine, 22(1). https://doi.org/10.1186/s12967-023-04798-w
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Picca, A., Di Stefano, A. L., Savatovsky, J., Ducray, F., Chinot, O., Moyal, E. C.-J., Augereau, P., Le Rhun, E., Schmitt, Y., Rousseaux, N., Yepnang, A. M. M., Estellat, C., Charbonneau, F., Letourneur, Q., Branger, D. F., Meyronet, D., Fardeau, C., Mokhtari, K., Bielle, F., … Sanson, M. (2024). TARGET: A phase I/II open-label multicenter study to assess safety and efficacy of fexagratinib in patients with relapsed/refractory FGFR fusion-positive glioma. Neuro-Oncology Advances, 6(1). https://doi.org/10.1093/noajnl/vdae068
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Columbia Affiliation
Dabbs, D. J., Chiriboga, L. A., Jasani, B., Kinloch, M. A., Miller, K. D., Nielsen, S., Szabolcs, M. J., Torlakovic, E., Bogen, S., Parry, S., & ‘t Hart, N. A. (2023). In Support of Magnani and Taylor. Archives of Pathology & Laboratory Medicine, 148(1), 11–11. https://doi.org/10.5858/arpa.2023-0446-le
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Prendergast, C. M., Lopci, E., Seban, R.-D., De Jong, D., Ammari, S., Aneja, S., Lévy, A., Sajan, A., Salvatore, M. M., Cappacione, K. M., Schwartz, L. H., Deutsch, E., & Dercle, L. (2023). Integrating [18F]-Fluorodeoxyglucose Positron Emission Tomography with Computed Tomography with Radiation Therapy and Immunomodulation in Precision Therapy for Solid Tumors. Cancers, 15(21), 5179. https://doi.org/10.3390/cancers15215179
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Rayn, K., Gupta, V., Mulinti, S., Clark, R., Magliari, A., Chaudhari, S., Gokhroo, G., & Beriwal, S. (2023). Evaluation of a Deep Image to Image Network (DI2IN) Auto-Segmentation Algorithm across a Network of Cancer Centers. International Journal of Radiation Oncology*Biology*Physics, 117(2), e711. https://doi.org/10.1016/j.ijrobp.2023.06.2209
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Dacic, S., Travis, W., Redman, M., Saqi, A., Cooper, W. A., Borczuk, A., Chung, J.-H., Glass, C., Lopez, J. M., Roden, A. C., Sholl, L., Weissferdt, A., Posadas, J., Walker, A., Zhu, H., Wijeratne, M. T., Connolly, C., Wynes, M., Bota-Rabassedas, N., … Wistuba, I. (2023). International Association for the Study of Lung Cancer Study of Reproducibility in Assessment of Pathologic Response in Resected Lung Cancers After Neoadjuvant Therapy. Journal of Thoracic Oncology, 18(10), 1290–1302. https://doi.org/10.1016/j.jtho.2023.07.017
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Zarabi, H., Helis, C. A., Russell, G., Huang, J., Liu, W., Soltys, S. G., Mendoza, M., Braunstein, S. E., Salans, M. A., Wang, T. J. C., Gallitto, M., Shi, W., Cappelli, L., Shen, C., Young, M. D., Mignano, J. E., Halasz, L. M., Barbour, A. B., Masters, A. H., & Chan, M. D. (2023). Multi-Institutional Report of Re-Irradiation for Recurrent High-Grade Glioma. International Journal of Radiation Oncology*Biology*Physics, 117(2), S85–S86. https://doi.org/10.1016/j.ijrobp.2023.06.408
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Ramkissoon, S. H., Fernandes, H., Lopez-Terrada, D. H., Hameed, M. R., Trembath, D. G., Bridge, J. A., Lindeman, N. I., Souers, R. J., Vasalos, P., Brat, D. J., & Moncur, J. T. (2022). Clinical Laboratory Testing Practices in Diffuse Gliomas Prior to Publication of 2021 World Health Organization Classification of Central Nervous System Tumors. Archives of Pathology & Laboratory Medicine, 147(5), 518–524. https://doi.org/10.5858/arpa.2021-0431-cp
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Dercle, L., Fronheiser, M., Rizvi, N. A., Hellmann, M. D., Maier, S., Hayes, W., Yang, H., Guo, P., Fojo, T., Schwartz, L. H., Zhao, B., & Leung, D. K. (2023). Baseline Radiomic Signature to Estimate Overall Survival in Patients With NSCLC. Journal of Thoracic Oncology, 18(5), 587–598. https://doi.org/10.1016/j.jtho.2022.12.019
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Weinstein, H. N. W., Lang, F. M., Barrett, C., Lampe, A., Sevensky, R., Fields, L., Leschly, K., Argenziano, M., & Rentrop, K. P. (2023). EFFECT OF REVASCULARIZATION VERSUS OPTIMAL MEDICAL THERAPY ALONE ON CORONARY FLOW CAPACITY DERIVED FROM SERIAL PET IMAGING STUDIES. Journal of the American College of Cardiology, 81(8), 1410. https://doi.org/10.1016/s0735-1097(23)01854-5
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Yeh, C., Zhou, M., Sigel, K., Jameson, G., White, R., Safyan, R., Saenger, Y., Hecht, E., Chabot, J., Schreibman, S., Juzyna, B., Ychou, M., Conroy, T., Fojo, T., Manji, G. A., Von Hoff, D., & Bates, S. E. (2022). Tumor Growth Rate Informs Treatment Efficacy in Metastatic Pancreatic Adenocarcinoma: Application of a Growth and Regression Model to Pivotal Trial and Real-World Data. The Oncologist, 28(2), 139–148. https://doi.org/10.1093/oncolo/oyac217
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Alkhafaji, H., & Ibrahim, A. (2022). Effects of Contrast Enhancement Phase on the Reproducibility and Predictivity of CT-Based Renal Lesions Radiomic Features. Applied Sciences, 12(24), 12599. https://doi.org/10.3390/app122412599
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Pan, Y., Wang, D., Chaudhary, M. F. A., Shao, W., Gerard, S. E., Durumeric, O. C., Bhatt, S. P., Barr, R. G., Hoffman, E. A., Reinhardt, J. M., & Christensen, G. E. (2022). Robust Measures of Image-Registration-Derived Lung Biomechanics in SPIROMICS. Journal of Imaging, 8(11), 309. https://doi.org/10.3390/jimaging8110309
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Galeano Niño, J. L., Wu, H., LaCourse, K. D., Kempchinsky, A. G., Baryiames, A., Barber, B., Futran, N., Houlton, J., Sather, C., Sicinska, E., Taylor, A., Minot, S. S., Johnston, C. D., & Bullman, S. (2022). Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer. Nature, 611(7937), 810–817. https://doi.org/10.1038/s41586-022-05435-0
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Pan, P., Joanta-Gomez, A., Yuen, C., Donovan, L., Haggiagi, A., Welch, M., Iwamoto, F., & Lassman, A. (2022). NCOG-24. TIME TO FIRST RECURRENCE AND SURVIVAL IN IDH-WILDTYPE GLIOBLASTOMA. Neuro-Oncology, 24(Supplement_7), vii202–vii202. https://doi.org/10.1093/neuonc/noac209.776
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Ibrahim, A., Lu, L., Yang, H., Akin, O., Schwartz, L. H., & Zhao, B. (2022). The Impact of Image Acquisition Parameters and ComBat Harmonization on the Predictive Performance of Radiomics: A Renal Cell Carcinoma Model. Applied Sciences, 12(19), 9824. https://doi.org/10.3390/app12199824
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Dercle, L., Gomez, D., Zhao, B., Kelly, K., Herbst, R. S., Redman, M. W., Gandara, D. R., & Schwartz, L. H. (2022). P2.12-03 External Validation of a Novel CT-Based Prognostic Radiomic Signature in Patients with Metastatic NSCLC in SWOG S0819 Phase III Randomized Trial. Journal of Thoracic Oncology, 17(9), S152. https://doi.org/10.1016/j.jtho.2022.07.251
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Hill, K., Miller, A. M., Li, B. K., Bouvier, N., Li, S., Alano, T., Doe-Tetteh, S., Huereca, C., DiNapoli, S., Lee, A., Szalontay, L., Riviere-Cazaux, C., Burns, T. C., Haque, S., Bale, T., Benhamida, J., Dogan, S., Vanderbilt, C., Ross, D., … Karajannis, M. (2022). PATH-16. Noninvasive diagnosis of gliomas through CSF cfDNA sequencing in pediatric and adolescent and young adult (AYA) patients. Neuro-Oncology, 24(Supplement_1), i162–i162. https://doi.org/10.1093/neuonc/noac079.600
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Webster Carrion, A., Wei, H.-J., McQuillan, N., Tazhibi, M., Kokossis, D., Berg, X., Minns, H., Zhang, X., Zhang, Z., Wang, J., Fernandez, E. C., Jan, C.-I., Padilla, O., Gartrell, R. D., Becher, O., Jr, J. H. G., Pavisic, J., Szalontay, L., Konofagou, E. E., … Wu, C.-C. (2022). MODL-24. Focused ultrasound-mediated blood-brain barrier opening and panobinostat in a thalamic syngeneic murine DMG model is feasible and safe. Neuro-Oncology, 24(Supplement_1), i174–i174. https://doi.org/10.1093/neuonc/noac079.647
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Brat, D. J., Aldape, K., Bridge, J. A., Canoll, P., Colman, H., Hameed, M. R., Harris, B. T., Hattab, E. M., Huse, J. T., Jenkins, R. B., Lopez-Terrada, D. H., McDonald, W. C., Rodriguez, F. J., Souter, L. H., Colasacco, C., Thomas, N. E., Yount, M. H., van den Bent, M. J., & Perry, A. (2022). Molecular Biomarker Testing for the Diagnosis of Diffuse Gliomas. Archives of Pathology & Laboratory Medicine, 146(5), 547–574. https://doi.org/10.5858/arpa.2021-0295-cp
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Refaee, T., Salahuddin, Z., Widaatalla, Y., Primakov, S., Woodruff, H. C., Hustinx, R., Mottaghy, F. M., Ibrahim, A., & Lambin, P. (2022). CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features. Journal of Personalized Medicine, 12(4), 553. https://doi.org/10.3390/jpm12040553
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