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Related Concept Videos

Detailed Structure and Function of Lymph Nodes01:23

Detailed Structure and Function of Lymph Nodes

Lymph nodes are bean-shaped structures that cluster along the lymphatic vessels in the inguinal, axillary, and cervical regions. Each node is divided into compartments by a capsule that extends trabeculae inward.
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Secondary Lymphoid Organs01:15

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The spleen is a vital organ in the lymphatic system, nestled in the upper left side of the abdomen. It is composed of two primary regions: the red pulp and the white pulp, each having distinct functions. The red pulp performs a significant role in blood filtration. It efficiently purges the blood of old or damaged red blood cells and...

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Single-port Non-liposuction Endoscopic Axillary Lymph Node Dissection in Breast Cancer Surgery
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Multi-modality morphological correlation of axillary lymph nodes.

Lina Arbash Meinel1, Hiroyuki Abe, Martin Bergtholdt

  • 1Philips Research of North America, Briarcliff Manor, NY, USA, lina.arbash-meinel@philips.com

International Journal of Computer Assisted Radiology and Surgery
|May 6, 2010
PubMed
Summary
This summary is machine-generated.

A new computerized method accurately correlates axillary lymph nodes (ALNs) between ultrasound (US) and breast MRI (BMRI), aiding non-invasive breast cancer staging. This multi-modality imaging approach enhances diagnostic accuracy for ALNs.

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Published on: August 9, 2019

Area of Science:

  • Medical Imaging
  • Oncology
  • Radiology

Background:

  • Accurate staging of breast cancer is crucial for effective treatment planning.
  • Axillary lymph node (ALN) status is a key prognostic factor.
  • Multi-modality imaging offers potential for improved non-invasive staging.

Purpose of the Study:

  • To develop a computerized method for correlating axillary lymph nodes (ALNs) between ultrasound (US) and breast MRI (BMRI).
  • To establish a preoperative, non-invasive method for breast cancer staging using multi-modality imaging.
  • To improve the accuracy of ALN evaluation in breast cancer patients.

Main Methods:

  • Utilized ultrasound (US) and breast MRI (BMRI) scans from 20 breast cancer patients.
  • Employed an ellipse fitting algorithm to segment ALN cortex and hilum for measurement of axes and maximum cortical thickness (MCT).
  • Computed Euclidean distances between US ALNs and candidate BMRI ALNs to determine the most likely correlation.

Main Results:

  • The computerized method successfully identified the same ALN as expert radiologists in 81.25% of cases (13 out of 16 ALNs).
  • Maximum cortical thickness (MCT) measurements showed small standard deviations and were comparable between US and MRI.
  • No significant differences were found in long axis, short axis, or MCT measurements between US and MRI-T2 weighted sequences.

Conclusions:

  • A feasibility study demonstrated that computerized measurements can correlate ALNs across different imaging modalities (US and BMRI).
  • This correlation enables the combined use of imaging parameters for ALN evaluation in breast cancer.
  • The multi-modality approach promises a more robust non-invasive method for axillary staging.