ArticleEuropean journal of nuclear medicine and molecular imaging2024
2-[
Article in European journal of nuclear medicine and molecular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- Targeting colorectal cancer and T‑cell metabolism for the treatment of colorectal cancer (Review).Oncology reports · 2026Review
- Combined dual-phase CT radiomics and deep transfer learning model for oxaliplatin response in unresectable colorectal liver metastases.Abdominal radiology (New York) · 2026Article
- Multimodal Management of Retroperitoneal Lymph Node Metastases in Colorectal Cancer: A Single-Center Retrospective Analysis.Annals of surgical oncology · 2026Article
- Diagnostic Performance of [World journal of nuclear medicine · 2025Review
- Predictive value of [European radiology · 2025Article
- A PET-CT radiomics model for immunotherapy response and prognosis prediction in patients with metastatic colorectal cancer.Frontiers in oncology · 2025Article
- Diagnostic Value of 18F-FDG PET/CT Parameters Combined with Serum FOXM1 for Lymph Node Metastasis in Colorectal Cancer.Clinical interventions in aging · 2025Article
- Synthesis, preclinical evaluation and pilot clinical translation of [European journal of nuclear medicine and molecular imaging · 2024Article
- Learning CT-free attenuation-corrected total-body PET images through deep learning.European radiology · 2024Article
- Surgical evidence-based comparison of [European journal of nuclear medicine and molecular imaging · 2024Article
- More than meets the eye: 2-[European journal of nuclear medicine and molecular imaging · 2024Article
- Single-cell aggrephagy-related patterns facilitate tumor microenvironment intercellular communication, influencing osteosarcoma progression and prognosis.Apoptosis : an international journal on programmed cell death · 2024Article
- [European journal of nuclear medicine and molecular imaging · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeThe pre-surgical estimation of lymph node (LN) metastasis in colorectal cancer (CRC) poses a significant diagnostic predicament. The associations between LN morphology, density, and metabolic heterogeneity and LN metastasis status in CRCs have been seldomly examined through the lens of radiomics. This research aimed to assess 2-[ MATERIALS AND
methodsThe construction of the model utilized data from 264 CRC patients, all of whom underwent preoperative 2-[
resultsThe radiomics model was composed of eight significant radiomic features (five from PET and three from CT), encapsulating metabolic and density heterogeneity. The radiomics signature (area under the curve (AUC), 0.908) showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.563, P < 0.001) and PET/CT-reported LN status (AUC, 0.64, P < 0.001) for predicting LN-positive or LN-negative status. The radiomics signature (AUC, 0.885) also showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.587, P < 0.001) and PET/CT-reported LN status (AUC, 0.621, P < 0.001) to identify N1 and N2. This signature maintained its independence from clinical risk factors and exhibited robustness in the validation test set. Decision curve analysis attested to the clinical utility of the radiomics signature.
conclusionsThe radiomics signature based on 2-[
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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.