ArticleInternational journal of computer assisted radiology and surgery2010
Multi-modality morphological correlation of axillary lymph nodes.
Article in International journal of computer assisted radiology and surgery, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 3 citations in OpenAlex.
- Quantitative ultrasound image analysis of axillary lymph node status in breast cancer patients.International journal of computer assisted radiology and surgery · 2013Article
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe goal of this study is to develop a computerized method that identifies a specific axillary lymph node (ALN) seen on ultrasound (US) with its most likely corresponding node on breast MRI (BMRI). This goal is an important step in developing a preoperative non-invasive method for staging breast cancer on the basis of multi-modality imaging.
methodsTwenty patients with newly diagnosed breast cancer were scanned on US and MRI. Two expert breast imaging radiologists independently correlated ALNs seen on US with BMRI, and this correlation was used as the gold standard. To correlate ALNs on US and BMRI, the cortex and hilum of each ALN was segmented using an ellipse fitting algorithm, then the ALN long and short axes and maximum cortical thickness (MCT) were computed. Three ALNs were chosen as candidates from the BMRI datasets for each lymph node seen on US. Finally, the Euclidean distances across all measurements between the US ALN and each of the three BMRI candidates were computed, and the smallest distance was reported as the correlation result.
resultsUsing the expert radiologists identified correlated BMRI slice as the ground truth, the shortest Euclidean distance successfully identified the same lymph node as the radiologists in 13 out of 16 ALNs (81.25%). In negative ALNs, the standard deviation for long and short axes was relatively large but that of maximum cortical thickness was small. Average maximum cortical thickness and its standard deviation measured in US were very close to those measured in MRI. There were no significant differences among the long axis, short axis, and MCT measurements between US and MRI-T2 weighted sequence (P > 0.05 paired t-test).
conclusionWe performed a feasibility study which showed that computerized measurements of ALNs might be used to identify the same ALN on different modalities such as US and BMRI. This type of correlation would be valuable as it would allow the use of combined imaging parameters to be applied to the evaluation of ALNs in patients with breast cancer. It is hoped that the combined multi-modality information would provide a more robust non-invasive method of staging the axilla than is currently available.
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