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Analysis of Lymph Node Volume by Ultra-High-Frequency Ultrasound Imaging in the Braf/Pten Genetically Engineered Mouse Model of Melanoma

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Three-dimensional quantitative ultrasound for detecting lymph node metastases.

Emi Saegusa-Beecroft¹, Junji Machi, Jonathan Mamou

¹Department of Surgery, University of Hawaii and Kuakini Medical Center, Honolulu, Hawaii 96817, USA. esaegusa@hawaii.edu

The Journal of Surgical Research

|January 22, 2013

Summary

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Quantitative ultrasound (QUS) effectively evaluates entire lymph nodes (LNs) for cancer metastases. This technology offers a reliable, operator-independent method to improve cancer detection and staging.

Area of Science:

Medical imaging
Oncology
Ultrasound technology

Background:

Lymph node (LN) metastasis detection is crucial for cancer management.
Conventional histology may fail to detect small metastatic foci within LNs.
A practical method for whole-LN volume evaluation is needed.

Purpose of the Study:

Develop fast, reliable, operator-independent quantitative ultrasound (QUS) methods.
Enable high-frequency, whole-volume evaluation of LNs for metastasis detection.

Main Methods:

Acquired 26 MHz echo-signal data from 146 colorectal, 26 gastric, and 118 breast cancer LNs.
Compared 13 QUS estimates with step-sectioned 50-μm histology.
Used linear-discriminant analysis for classification and receiver-operator characteristic curves (Az) to assess performance.

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Generated 3D cancer probability images from QUS data.

Main Results:

High diagnostic performance for colorectal (Az=0.952), gastric (Az=0.962), and breast (Az=0.833) cancer LNs.
Achieved high sensitivity and specificity, with some cases reaching 100% sensitivity.
Demonstrated good correlation between 3D QUS cancer probability images and 3D histology.

Conclusions:

Operator- and system-independent QUS methods enable reliable, whole-volume LN evaluation for metastasis detection.
3D cancer probability imaging aids pathologists in identifying potentially missed metastatic foci.
QUS offers a promising advancement over conventional methods for LN metastasis assessment.