PubMed Mentions
The links below are to publications on PubMed referring to The Cancer Imaging Archive (TCIA). This list is gathered weekly from PubMed automatically and was last updated on October 20, 2025.
| Publication/References | |
| Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas. Description: Jiang, Chendan, et al. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas. ''Eur J Radiol''. 2019 Dec; '''121''': 108714 | |
| Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework. Description: Ibrahim, A, et al. Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework. ''Methods''. 2021 Apr; '''188''': 20-29 | |
| The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. Description: Rodriguez, Henry, et al. The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment. ''Cell''. 2021 Apr 1; '''184''' (7):1661-1670 | |
| Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer. Description: Zeng, Hao, et al. Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer. ''Gynecol Oncol''. 2021 Oct; '''163''' (1):171-180 | |
| Development and verification of radiomics framework for computed tomography image segmentation. Description: Gu, Jiabing, et al. Development and verification of radiomics framework for computed tomography image segmentation. ''Med Phys''. 2022 Oct; '''49''' (10):6527-6537 | |
| Patient-Specific Magnetic Catheters for Atraumatic Autonomous Endoscopy. Description: Pittiglio, Giovanni, et al. Patient-Specific Magnetic Catheters for Atraumatic Autonomous Endoscopy. ''Soft Robot''. 2022 Dec; '''9''' (6):1120-1133 | |
| The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy. Description: Crombe, Amandine, et al. The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy. ''Cancer Commun (Lond)''. 2022 Dec; '''42''' (12):1288-1313 | |
| An intravenous pancreatic cancer therapeutic: Characterization of CRISPR/Cas9n-modified Clostridium novyi-Non Toxic. Description: Dailey, Kaitlin M, et al. An intravenous pancreatic cancer therapeutic: Characterization of CRISPR/Cas9n-modified Clostridium novyi-Non Toxic. ''PLoS One''. 2023; '''18''' (11):e0289183 | |
| Comparison of MRI radiomics-based machine learning survival models in predicting prognosis of glioblastoma multiforme. Description: Zhang, Di, et al. Comparison of MRI radiomics-based machine learning survival models in predicting prognosis of glioblastoma multiforme. ''Front Med (Lausanne)''. 2023; '''10''': 1271687 | |
| CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma. Description: He, Zenglei, et al. CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma. ''PLoS One''. 2023; '''18''' (9):e0290900 | |
| Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients. Description: Dammu, Hongyi, et al. Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients. ''PLoS One''. 2023; '''18''' (1):e0280148 | |
| SIFT-GVF-based lung edge correction method for correcting the lung region in CT images. Description: Li, Xin, et al. SIFT-GVF-based lung edge correction method for correcting the lung region in CT images. ''PLoS One''. 2023; '''18''' (2):e0282107 | |
| The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma. Description: Bao, Hongbo, et al. The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma. ''Front Neurol''. 2023; '''14''': 1264322 | |
| Translating Data Science Results into Precision Oncology Decisions: A Mini Review. Description: Capobianco, Enrico, et al. Translating Data Science Results into Precision Oncology Decisions: A Mini Review. ''J Clin Med''. 2023 Jan 5; '''12''' (2): | |
| Molecular hallmarks of breast multiparametric magnetic resonance imaging during neoadjuvant chemotherapy. Description: Lin, Peng, et al. Molecular hallmarks of breast multiparametric magnetic resonance imaging during neoadjuvant chemotherapy. ''Radiol Med''. 2023 Jan 21; 1-13 | |
| Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer. Description: Liu, Qian, et al. Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer. ''Biomark Res''. 2023 Jan 24; '''11''' (1):9 | |
| Prognostic value of (18)F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer. Description: Wang, Bingzhen, et al. Prognostic value of (18)F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer. ''EJNMMI Res''. 2023 Feb 13; '''13''' (1):14 | |
| Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma. Description: He, Hongchao, et al. Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma. ''Cancer Med''. 2023 Mar; '''12''' (6):7627-7638 | |
| New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction. Description: Bao, Hongbo, et al. New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction. ''Int J Cancer''. 2023 Mar 1; '''152''' (5):998-1012 | |
| Fully-automated sarcopenia assessment in head and neck cancer: development and external validation of a deep learning pipeline. Description: Ye, Zezhong, et al. Fully-automated sarcopenia assessment in head and neck cancer: development and external validation of a deep learning pipeline. ''medRxiv''. 2023 Mar 6; | |
| An Online Mammography Database with Biopsy Confirmed Types. Description: Cai, Hongmin, et al. An Online Mammography Database with Biopsy Confirmed Types. ''Sci Data''. 2023 Mar 7; '''10''' (1):123 | |
| Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study. Description: Lavinia Loeffler, Chiara Maria, et al. Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study. ''medRxiv''. 2023 Mar 10; | |
| An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma. Description: Han, Tao, et al. An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma. ''Sci Rep''. 2023 Mar 29; '''13''' (1):5153 | |
| MTF1 has the potential as a diagnostic and prognostic marker for gastric cancer and is associated with good prognosis. Description: He, Jin, et al. MTF1 has the potential as a diagnostic and prognostic marker for gastric cancer and is associated with good prognosis. ''Clin Transl Oncol''. 2023 Apr 24; 1-11 | |
| Clinical applications of artificial intelligence in radiology. Description: Mello-Thoms, Claudia, et al. Clinical applications of artificial intelligence in radiology. ''Br J Radiol''. 2023 Apr 26; '''96''' (1150):20221031 | |
| Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features. Description: Wang, Fen, et al. Comparison and fusion prediction model for lung adenocarcinoma with micropapillary and solid pattern using clinicoradiographic, radiomics and deep learning features. ''Sci Rep''. 2023 Jun 8; '''13''' (1):9302 | |
| Assessment of brain cancer atlas maps with multimodal imaging features. Description: Capobianco, Enrico, et al. Assessment of brain cancer atlas maps with multimodal imaging features. ''J Transl Med''. 2023 Jun 12; '''21''' (1):385 | |
| Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learning. Description: Boyd, Aidan, et al. Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learning. ''medRxiv''. 2023 Jun 30; | |
| HLA-DQA1 expression is associated with prognosis and predictable with radiomics in breast cancer. Description: Zhou, JingYu, et al. HLA-DQA1 expression is associated with prognosis and predictable with radiomics in breast cancer. ''Radiat Oncol''. 2023 Jul 11; '''18''' (1):117 | |
| Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. Description: Lu, Haonan, et al. Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer. ''Cell Rep Med''. 2023 Jul 18; '''4''' (7):101092 | |
| Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System. Description: Lee, So Jeong, et al. Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System. ''Korean J Radiol''. 2023 Aug; '''24''' (8):772-783 | |
| SAMPLER: Empirical distribution representations for rapid analysis of whole slide tissue images. Description: Mukashyaka, Patience, et al. SAMPLER: Empirical distribution representations for rapid analysis of whole slide tissue images. ''bioRxiv''. 2023 Aug 3; | |
| SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers. Description: Al-Tashi, Qasem, et al. SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers. ''Patterns (N Y)''. 2023 Aug 11; '''4''' (8):100777 | |
| CT radiomics prediction of CXCL9 expression and survival in ovarian cancer. Description: Gu, Rui, et al. CT radiomics prediction of CXCL9 expression and survival in ovarian cancer. ''J Ovarian Res''. 2023 Aug 30; '''16''' (1):180 | |
| A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information. Description: Ramakrishnan, Divya, et al. A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information. ''ArXiv''. 2023 Sep 12; | |
| Prediction of cancer treatment response from histopathology images through imputed transcriptomics. Description: Hoang, Danh-Tai, et al. Prediction of cancer treatment response from histopathology images through imputed transcriptomics. ''Res Sq''. 2023 Sep 15; | |
| A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer. Description: Zhan, Feng, et al. A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer. ''Sci Rep''. 2023 Sep 29; '''13''' (1):16397 | |
| Radiological Study of Atlas Arch Defects with Meta-Analysis and a Proposed New Classification. Description: Suphamungmee, Worawit, et al. Radiological Study of Atlas Arch Defects with Meta-Analysis and a Proposed New Classification. ''Asian Spine J''. 2023 Oct; '''17''' (5):975-984 | |
| ARPC5 acts as a potential prognostic biomarker that is associated with cell proliferation, migration and immune infiltrate in gliomas. Description: Ming, Yue, et al. ARPC5 acts as a potential prognostic biomarker that is associated with cell proliferation, migration and immune infiltrate in gliomas. ''BMC Cancer''. 2023 Oct 3; '''23''' (1):937 | |
| Noninvasive radiomic analysis of enhanced CT predicts CTLA4 expression and prognosis in head and neck squamous cell carcinoma. Description: Zhu, Yeping, et al. Noninvasive radiomic analysis of enhanced CT predicts CTLA4 expression and prognosis in head and neck squamous cell carcinoma. ''Sci Rep''. 2023 Oct 5; '''13''' (1):16782 | |
| Association of graph-based spatial features with overall survival status of glioblastoma patients. Description: Lee, Joonsang, et al. Association of graph-based spatial features with overall survival status of glioblastoma patients. ''Sci Rep''. 2023 Oct 9; '''13''' (1):17046 | |
| CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. Description: Xia, Tian, et al. CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. ''J Digit Imaging''. 2023 Dec; '''36''' (6):2356-2366 | |
| Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics. Description: Jiang, Wenying, et al. Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics. ''Cancer Med''. 2023 Dec; '''12''' (24):21861-21872 | |
| Deep learning-based segmentation of multisite disease in ovarian cancer. Description: Buddenkotte, Thomas, et al. Deep learning-based segmentation of multisite disease in ovarian cancer. ''Eur Radiol Exp''. 2023 Dec 7; '''7''' (1):77 | |
| Lesion detection in women breast's dynamic contrast-enhanced magnetic resonance imaging using deep learning. Description: Saikia, Sudarshan, et al. Lesion detection in women breast's dynamic contrast-enhanced magnetic resonance imaging using deep learning. ''Sci Rep''. 2023 Dec 18; '''13''' (1):22555 | |
| Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital. Description: Kulkarni, Chaitanya, et al. Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital. ''BJR Open''. 2024 Jan; '''6''' (1):tzad008 | |
| Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. Description: Wiltgen, Tun, et al. Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. ''PLoS One''. 2024; '''19''' (3):e0298642 | |
| Use of fractals in determining the malignancy degree of lung nodules. Description: Amador-Legon, Noel Victor, et al. Use of fractals in determining the malignancy degree of lung nodules. ''Front Med Technol''. 2024; '''6''': 1362688 | |
| Focus stacking single-event particle radiography for high spatial resolution images and 3D feature localization. Description: Volz, Lennart, et al. Focus stacking single-event particle radiography for high spatial resolution images and 3D feature localization. ''Phys Med Biol''. 2024 Jan 10; '''69''' (2): | |
| A comparative analysis of CNN-based deep learning architectures for early diagnosis of bone cancer using CT images. Description: Sampath, Kanimozhi, et al. A comparative analysis of CNN-based deep learning architectures for early diagnosis of bone cancer using CT images. ''Sci Rep''. 2024 Jan 25; '''14''' (1):2144 | |
| Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme. Description: Luan, Jixin, et al. Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme. ''J Transl Med''. 2024 Jan 26; '''22''' (1):107 | |
| MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma. Description: Chen, Di, et al. MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma. ''Biomark Res''. 2024 Jan 31; '''12''' (1):14 | |
| A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring. Description: Connor, Kate, et al. A clinically relevant computed tomography (CT) radiomics strategy for intracranial rodent brain tumour monitoring. ''Sci Rep''. 2024 Feb 1; '''14''' (1):2720 | |
| Development of End-to-End AI-Based MRI Image Analysis System for Predicting IDH Mutation Status of Patients with Gliomas: Multicentric Validation. Description: Santinha, Joao, et al. Development of End-to-End AI-Based MRI Image Analysis System for Predicting IDH Mutation Status of Patients with Gliomas: Multicentric Validation. ''J Imaging Inform Med''. 2024 Feb; '''37''' (1):31-44 | |
| A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI. Description: Wei, Ruili, et al. A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI. ''J Cancer Res Clin Oncol''. 2024 Feb 2; '''150''' (2):73 | |
| Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis. Description: Boubnovski Martell, Marc, et al. Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis. ''NPJ Precis Oncol''. 2024 Feb 3; '''8''' (1):28 | |
| AI applications in musculoskeletal imaging: a narrative review. Description: Gitto, Salvatore, et al. AI applications in musculoskeletal imaging: a narrative review. ''Eur Radiol Exp''. 2024 Feb 15; '''8''' (1):22 | |
| CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer. Description: Wang, Jiexiao, et al. CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer. ''BMC Med Imaging''. 2024 Feb 15; '''24''' (1):45 | |
| Reducing image artifacts in sparse projection CT using conditional generative adversarial networks. Description: Usui, Keisuke, et al. Reducing image artifacts in sparse projection CT using conditional generative adversarial networks. ''Sci Rep''. 2024 Feb 16; '''14''' (1):3917 | |
| CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies. Description: Gitto, Salvatore, et al. CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies. ''Insights Imaging''. 2024 Feb 27; '''15''' (1):54 | |
| A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. Description: Ramakrishnan, Divya, et al. A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information. ''Sci Data''. 2024 Feb 29; '''11''' (1):254 | |
| Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer. Description: Huang, Zi Huai, et al. Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer. ''J Transl Med''. 2024 Mar 2; '''22''' (1):226 | |
| Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept. Description: Salehjahromi, Morteza, et al. Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept. ''Cell Rep Med''. 2024 Mar 19; '''5''' (3):101463 | |
| Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response. Description: Chen, Ziqiang, et al. Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response. ''NPJ Precis Oncol''. 2024 Mar 22; '''8''' (1):73 | |
| A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study. Description: Lai, Jianguo, et al. A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study. ''Int J Surg''. 2024 Apr 1; '''110''' (4):2162-2177 | |
| Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study. Description: Chen, Siteng, et al. Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study. ''Int J Surg''. 2024 May 1; '''110''' (5):2970-2977 | |
| Risk assessment model based on nucleotide metabolism-related genes highlights SLC27A2 as a potential therapeutic target in breast cancer. Description: Zhang, Bo, et al. Risk assessment model based on nucleotide metabolism-related genes highlights SLC27A2 as a potential therapeutic target in breast cancer. ''J Cancer Res Clin Oncol''. 2024 May 16; '''150''' (5):258 | |
| Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images. Description: Shahram, Mohammad Amin, et al. Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images. ''BMC Neurosci''. 2024 May 25; '''25''' (1):26 | |
| Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics. Description: Zhang, Chen, et al. Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics. ''J Ovarian Res''. 2024 Jun 22; '''17''' (1):131 |