ArticleQuantitative imaging in medicine and surgery2021
Preoperative volumetric synthetic magnetic resonance imaging of the primary tumor for a more accurate prediction of lymph node metastasis in rectal cancer.
Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 33 citations in OpenAlex.
- Preoperative synthetic magnetic resonance imaging-based biomarkers for predicting tumor budding of rectal cancer.BMC medical imaging · 2026Article
- An Interpretable Machine Learning Model With Synthetic MRI-Based Habitat Radiomics for Predicting Lymph Node Metastasis in Oral Cancer.Cancer medicine · 2026Article
- Quantitative assessment of benign and malignant bone tumours using synthetic magnetic resonance imaging and diffusion measures.Scientific reports · 2025Article
- Whole-tumor histogram analysis of synthetic MRI for discriminating benign from malignant sinonasal tumors: correlations with histopathologic factors.Quantitative imaging in medicine and surgery · 2025Article
- Whole-tumor histogram analysis of synthetic magnetic resonance imaging predicts isocitrate dehydrogenase mutation status in gliomas.Quantitative imaging in medicine and surgery · 2024Article
- Radiomics in rectal cancer: current status of use and advances in research.Frontiers in oncology · 2024Review
- Pretreatment synthetic magnetic resonance imaging predicts disease progression in nonmetastatic nasopharyngeal carcinoma after intensity modulation radiation therapy.Insights into imaging · 2023Article
- Fundamentals of Bowel Cancer for Biomedical Engineers.Annals of biomedical engineering · 2023Review
- The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study.BMC medical imaging · 2023Article
- Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.Quantitative imaging in medicine and surgery · 2022Article
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6 authors at 2 institutions in 1 country.
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Abstract
backgroundAn accurate assessment of lymph node (LN) status in patients with rectal cancer is important for treatment planning and an essential factor for predicting local recurrence and overall survival. In this study, we explored the potential value of histogram parameters of synthetic magnetic resonance imaging (SyMRI) in predicting LN metastasis in rectal cancer and compared their predictive performance with traditional morphological characteristics and chemical shift effect (CSE).
methodsA total of 70 patients with pathologically proven rectal adenocarcinoma who received direct surgical resection were enrolled in this prospective study. Preoperative rectal MRI, including SyMRI, were performed, and morphological characteristics and CSE of LN were assessed. Histogram parameters were extracted on a T1 map, T2 map, and proton density (PD) map, including mean, variance, maximum, minimum, 10th percentile, median, 90th percentile, energy, kurtosis, entropy, and skewness. Receiver operating characteristic (ROC) curves were used to explore their predictive performance for assessing LN status.
resultsSignificant differences in the energy of the T1, T2, and PD maps were observed between LN-negative and LN-positive groups [all P<0.001; the area under the ROC curve (AUC) was 0.838, 0.858, and 0.823, respectively]. The maximum and kurtosis of the T2 map, maximum, and variance of PD map could also predict LN metastasis with moderate diagnostic power (P=0.032, 0.045, 0.016, and 0.047, respectively). Energy of the T1 map [odds ratio (OR) =1.683, 95% confidence interval (CI): 1.207-2.346, P=0.002] and extramural venous invasion on MRI (mrEMVI) (OR =10.853, 95% CI: 2.339-50.364, P=0.002) were significant predictors of LN metastasis. Moreover, the T1 map energy significantly improved the predictive performance compared to morphological features and CSE (P=0.0002 and 0.0485).
conclusionsThe histogram parameters derived from SyMRI of the primary tumor were associated with LN metastasis in rectal cancer and could significantly improve the predictive performance compared with morphological features and CSE.
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