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.
| 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 |