ArticleChronic diseases and translational medicine2018
Quantitative image analysis for evaluation of tumor response in clinical oncology.
Article in Chronic diseases and translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
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- Fully automated volumetry of ventricular subregions on computed tomography using object detection and semantic segmentation.Neuroimage. Reports · 2026Article
- Deep-Learning Serial CT Prediction of Survival in Immunotherapy-Treated Non-Small Cell Lung Cancer.JAMA network open · 2026Article
- CT-based radiomic prognostic vector (RPV) predicts survival and stromal histology in high-grade serous ovarian cancer: an external validation study.European radiology · 2025Article
- Harnessing Artificial Intelligence in Pediatric Oncology Diagnosis and Treatment: A Review.Cancers · 2025Review
- Urinary IR700 Ligand as an Early Biomarker of Therapeutic Efficacy of Near-Infrared Photoimmunotherapy.ACS omega · 2025Article
- Radiomics-Based Prediction of Treatment Response to TRuC-T Cell Therapy in Patients with Mesothelioma: A Pilot Study.Cancers · 2025Article
- Robust radiomics: a review of guidelines for radiomics in medical imaging.Frontiers in radiology · 2025Review
- Rapid Polyp Classification in Colonoscopy Using Textural and Convolutional Features.Healthcare (Basel, Switzerland) · 2022Article
- The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics.Journal of imaging · 2021Article
- Quantitative ultrasound shear wave elastography (USWE)-measured tissue stiffness correlates with PIRADS scoring of MRI and Gleason score on whole-mount histopathology of prostate cancer: implications for ultrasound image-guided targeting approach.Insights into imaging · 2021Article
- Exploring the Interobserver Agreement in Computer-Aided Radiologic Tumor Measurement and Evaluation of Tumor Response.Frontiers in oncology · 2021Article
- Article
- MRI image analysis methods and applications: an algorithmic perspective using brain tumors as an exemplar.Neuro-oncology advancesReview
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Authors and funding
2 authors.
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Abstract
The objective, accurate, and standardized evaluation of tumor response to treatment is an indispensable procedure in clinical oncology. Compared to manual measurement, computer-assisted linear measurement can significantly improve the accuracy and reproducibility of tumor burden quantification. For irregular-shaped and infiltrating or diffuse tumors, which are difficult to quantify by linear measurement, computer-assisted volumetric measurement may provide a more objective and sensitive quantification to evaluate tumor response to treatment than linear measurement does. In the evaluation of tumor response to novel oncologic treatments such as targeted therapy, changes in overall tumor size do not necessarily reflect tumor response to therapy due to the presence of internal necrosis or hemorrhages. This leads to a new generation of imaging biomarkers to evaluate tumor response by using texture analysis methods, also called radiomics. Computer-assisted texture analysis technology offers a more comprehensive and in-depth imaging biomarker to evaluate tumor response. The application of computer-assisted quantitative imaging analysis techniques not only reduces the inaccuracy and improves the reliability in tumor burden quantification, but facilitates the development of more comprehensive and intelligent approaches to evaluate treatment response, and hence promotes precision imaging in the evaluation of tumor response in clinical oncology. This article summarizes the state-of-the-art technical developments and clinical applications of quantitative imaging analysis in evaluation of tumor response in clinical oncology.
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