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Assessing Body Temperature - Axilla01:14

Assessing Body Temperature - Axilla

Procedural Guide for Assessing Axillary Body Temperature using a Digital Thermometer:
Step 1: Perform hand hygiene and put on clean gloves to maintain infection control and prevent cross-contamination.
Step 2: Prepare the patient by explaining the procedure to ensure understanding and cooperation. Ensure privacy, expose the axilla, and inform the patient that minimal movement is crucial for an accurate reading.
Step 3: Adjust the patient’s clothing to expose only the axilla. It minimizes...

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Related Experiment Video

Updated: Jul 3, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

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Breast Cancer Screening Using Inverse Modeling of Surface Temperatures and Steady-State Thermal Imaging.

Nithya Sritharan1, Carlos Gutierrez2, Isaac Perez-Raya2,3

  • 1Department of Hematology-Oncology, Rochester Regional Health, Rochester, NY 14621, USA.

Cancers
|June 27, 2024
PubMed
Summary

This study used infrared thermography and inverse modeling to accurately predict breast cancer in 25 patients. The technique shows promise for non-invasive breast cancer screening.

Keywords:
breast cancer screeningheat generation mapinverse modelingphysics-informed neural network

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Area of Science:

  • Oncology
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Cancer exhibits altered metabolic activity and vascularity, causing distinct temperature variations in malignant tissues.
  • Early and accurate breast cancer detection is crucial for effective treatment and improved patient outcomes.

Purpose of the Study:

  • To evaluate the efficacy of an ultra-high sensitivity thermal camera combined with inverse modeling for predicting malignant breast lesions.
  • To assess the technique's accuracy irrespective of tumor characteristics like size, location, or breast density.

Main Methods:

  • Patients with abnormal mammograms or clinical suspicion of breast cancer, confirmed by biopsy, were included.
  • Surface temperatures were measured using an ultra-high sensitivity thermal camera with prone positioning.
  • An inverse modeling technique based on heat transfer principles was employed to predict tumor characteristics.

Main Results:

  • The technique accurately predicted all 25 breast tumors analyzed.
  • Maximum prediction errors for tumor size were below 5 mm, and for location, less than 1 cm.
  • Predictive accuracy remained consistent across varying tumor sizes, locations, and breast densities, with no false positives in the contralateral breast.

Conclusions:

  • Infrared temperature profiling coupled with inverse modeling is a successful method for predicting breast cancer.
  • This non-invasive approach demonstrates significant potential as a complementary tool in breast cancer screening protocols.