ArticleCancers2020
Extended Texture Analysis of Non-Enhanced Whole-Body MRI Image Data for Response Assessment in Multiple Myeloma Patients Undergoing Systemic Therapy.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 46 citations in OpenAlex.
- Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma.Journal of cancer research and clinical oncology · 2023Trial
- U-Swing: An Adaptive U-Net and Swin Fusion for WB-MRI Whole Spine Bone Marrow Segmentation.Journal of imaging informatics in medicine · 2026Article
- Machine learning and quantitative computed tomography radiomics prediction of postoperative functional recovery in paraplegic dogs.Veterinary surgery : VS · 2025Article
- Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: A two-center study.Journal of bone oncology · 2024Article
- Quantitative assessment of bone marrow infiltration and characterization of tumor burden using dual-layer spectral CT in patients with multiple myeloma.Radiology and oncology · 2024Article
- Imaging of Multiple Myeloma: Present and Future.Journal of clinical medicine · 2024Review
- Application of a Radiomics Machine Learning Model for Differentiating Aldosterone-Producing Adenoma from Non-Functioning Adrenal Adenoma.Bioengineering (Basel, Switzerland) · 2023Article
- Lumbar MR-based radiomics nomogram for detecting minimal residual disease in patients with multiple myeloma.European radiology · 2023Article
- MRI radiomics-based evaluation of tuberculous and brucella spondylitis.The Journal of international medical research · 2023Article
- Radiomics Analysis for Multiple Myeloma: A Systematic Review with Radiomics Quality Scoring.Diagnostics (Basel, Switzerland) · 2023Review
- Machine Learning Model Based on Optimized Radiomics Feature fromJournal of clinical medicine · 2023Article
- Non-Contrast CT-Based Radiomics Score for Predicting Hematoma Enlargement in Spontaneous Intracerebral Hemorrhage.Clinical neuroradiology · 2022Article
- Radiomics Models Based on Magnetic Resonance Imaging for Prediction of the Response to Bortezomib-Based Therapy in Patients with Multiple Myeloma.BioMed research international · 2022Article
- Radiomics-based nomogram as predictive model for prognosis of hepatocellular carcinoma with portal vein tumor thrombosis receiving radiotherapy.Frontiers in oncology · 2022Article
- [Potential of radiomics and artificial intelligence in myeloma imaging : Development of automatic, comprehensive, objective skeletal analyses from whole-body imaging data].Der Radiologe · 2022Review
- Radiation Versus Immune Checkpoint Inhibitor Associated Pneumonitis: Distinct Radiologic Morphologies.The oncologist · 2021Article
- Radiomics and Artificial Intelligence for Outcome Prediction in Multiple Myeloma Patients Undergoing Autologous Transplantation: A Feasibility Study with CT Data.Diagnostics (Basel, Switzerland) · 2021Article
- A preliminary study using spinal MRI-based radiomics to predict high-risk cytogenetic abnormalities in multiple myeloma.La Radiologia medica · 2021Article
- Imaging in multiple myeloma: Computed tomography or magnetic resonance imaging?World journal of radiology · 2021Article
- Correlations between apparent diffusion coefficient values of WB-DWI and clinical parameters in multiple myeloma.BMC medical imaging · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying MRI-based radiomics features capable to assess response to systemic treatment in multiple myeloma (MM) patients. Retrospective analysis of whole-body MR-image data in 67 consecutive stage III MM patients (40 men; mean age, 60.4 years). Bone marrow involvement was evaluated using a standardized MR-imaging protocol consisting of T1w-, short-tau inversion recovery- (STIR-) and diffusion-weighted-imaging (DWI) sequences. Ninety-two radiomics features were evaluated, both in focally and diffusely involved bone marrow. Volumes of interest (VOI) were used. Response to treatment was classified according to International Myeloma Working Group (IMWG) criteria in complete response (CR), very-good and/or partial response (VGPR + PR), and non-response (stable disease (SD) and progressive disease (PD)). According to the IMWG-criteria, response categories were CR (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.