ArticleQuantitative imaging in medicine and surgery2022
Iodine map histogram metrics in early-stage breast cancer: prediction of axillary lymph node metastasis status.
Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Whole-volume histogram analysis of spectral-computed tomography iodine maps characterizes HER2 expression in gastric cancer.World journal of gastroenterology · 2024Trial
- Value of Radiomics Based on DCE-MRI in distinguishing benign and malignant breast lesions: Predicting Histological Grade and Lymph Node Metastasis of Breast Cancer.Pakistan journal of medical sciences · 2026Article
- Preoperative contrast-enhanced CT for predicting the macrotrabecular-massive subtype and its prognostic significance in hepatocellular carcinoma.Quantitative imaging in medicine and surgery · 2025Article
- A comparative study of dual-layer spectral CT and 18F-FDG-PET/CT multi-quantitative parameters in the diagnosis of sentinel lymph nodes in breast cancer.Annals of nuclear medicine · 2025Article
- Prediction of Ki-67 expression in gastric gastrointestinal stromal tumors using histogram analysis of monochromatic and iodine images derived from spectral CT.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- A prediction model based on dual-layer spectral detector computed tomography for distinguishing nonluminal from luminal invasive breast cancer.Quantitative imaging in medicine and surgery · 2024Article
- Whole-lesion iodine map histogram analysis in the risk classification of gastrointestinal stromal tumors: comparison with single-slice iodine concentration measurements.Abdominal radiology (New York) · 2024Article
- Differentiating angiomatous meningioma from atypical meningioma using histogram analysis of apparent diffusion coefficient maps.Quantitative imaging in medicine and surgery · 2023Article
- Differentiating gastric schwannoma from gastric stromal tumor (≤5 cm) by histogram analysis based on iodine-based material decomposition images: a preliminary study.Frontiers in oncology · 2023Article
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Authors and funding
8 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Variations in axillary lymph node (ALN) metastatic potential between different breast cancers lead to microscopical alterations in tumor perfusion heterogeneity. This study investigated the usefulness of histogram metrics from iodine maps in the preoperative diagnosis of metastatic ALNs in patients with early-stage breast cancer. Methods: Between October 2020 and November 2021 enhanced spectral computed tomography (CT) was performed in female patients with breast cancer. Quantitative spectral CT parameters and histogram parameters (mean, median, maximum, minimum, 10th percentiles, 90th percentiles, kurtosis, skewness, energy, range, and variance) from iodine maps were compared between patients with metastatic and nonmetastatic ALNs. Continuous variables were compared using Student's Results: This study included 113 female patients (62 and 51 in the ALN-negative and ALN-positive groups, respectively). Tumor size, molecular subtypes, and location differed significantly between the ALN-negative and ALN-positive groups (P<0.05). None of the quantitative spectral CT parameters of mass between metastatic and nonmetastatic ALN groups were significantly different (P>0.05). Histogram parameters of iodine maps for breast cancers, including maximum, 10th percentile, range, and energy, were significantly higher in the metastatic ALNs group compared with the nonmetastatic ALNs group (P<0.05). Multivariable logistic regression analyses showed that tumor location and energy were independent predictors of metastatic ALNs in breast cancers. The combination of independent predictors yielded an area under the curve (AUC) of 0.824 (sensitivity 72.5%; specificity 74.2%). Conclusions: Whole-lesion histogram parameters derived from spectral CT iodine maps may be used as a complementary noninvasive means for the preoperative identification of ALN metastases in patients with early-stage breast cancer.
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