The ability to assess the impact of radiation on malignant tumors during a course of radiotherapy could help improve its effectiveness for individual patients. Based on tumor response, physicians could modify the treatment regimen and the radiation field.

Israeli researchers have now demonstrated that thermography may provide a viable radiotherapy monitoring tool for such treatment optimization. They have developed a method to detect tumors in a thermal image and estimate changes in tumor and vasculature during radiotherapy, validating this in a study of six patients with advanced breast cancer.

Thermography had been rejected as a breast cancer detection tool, due to its suboptimal sensitivity and specificity. However, for an already detected tumour undergoing radiation or chemotherapy, it could prove a highly effective monitoring tool, when incorporating algorithms developed by the research team.

The multi-institutional team had conducted research on thermal imaging to understand tumour aggressiveness in animal models. They hypothesized that because abnormal metabolic and perfusion rates characterize malignant tumors, they will generate a different temperature distribution pattern compared with healthy tissue.

By measuring skin temperature maps at the tumor location before and during treatment, the reaction of a tumor to radiotherapy can be measured. Israel Gannot from Tel-Aviv University and co-authors developed a four-step algorithm to analyze the thermal images.

First, images were converted from color to grey scale and a fixed temperature range of 7°C set for all images, to enable comparison of the entropy (which characterizes the homogeneity of the image) in different images. Images were filtered using a Frangi filter designed to emphasize tubular structures.

This filter highlighted blobs of heat (a malignant tumor) and long, narrow tubular objects (the blood vessel network). Images were enlarged sevenfold to observe local temperature changes in the blood vessels.

In the final step, feature extraction, the algorithm calculates entropy in the cropped thermal image of the tumor area and the filtered tumor image. It then estimates changes in tumor regularity and vasculature shape during radiotherapy.

Patient imaging

The six patients were women with stage IV breast cancer and distant metastatic disease. None had undergone surgical resection of their tumors, which had a diameter larger than 1 cm at a depth of less than 1 cm. All patients received 15 radiation fractions of 3 Gy, administered over three weeks.

The patients underwent thermal imaging before each radiotherapy session and a day after the end of the session. Room temperature and humidity were controlled during image acquisition, and fluorescent lights were turned off.

The authors report that entropy was reduced in the tumor areas, for all patients, during radiation treatment. They described the appearance of the tumor vasculature as “a crab with many arms.”

To quantify changes in the shape of vascular networks, they converted the images into binary images and counted the number of objects before and after radiotherapy. They saw a reduction in the number of objects, indicating a reduction in the vessels supplying nutrients to a tumor.