Abstract
Objective. Quality assurance of hyperthermia applicators can be a
cumbersome task. Periodic validation of the fields generated by the
applicator is crucial for ensuring proper device performance, but the
required measurements are very time-consuming. While most clinics use
heating rate as a parameter of interest, consensus exists that spatial
variation of the electromagnetic field in three dimensions (3D) would be
much more insightful. Unfortunately, such 3D coverage would require
measurements at many locations. Approach. To address this
challenge, we propose a compressed sensing based methodology that
enables accurate E-field and specific absorption rate (SAR)
reconstruction from significantly reduced sampling densities. Using a
Lucite Cone Applicator (LCA) and a homogeneous tissue-mimicking phantom,
E-field measurements were obtained via a robotic scanning system
equipped with an isotropic EM field probe (EX3DV4, SPEAG). Field maps
were reconstructed using a discrete cosine transform (DCT)-based
compressed sensing algorithm and evaluated using peak signal-to-noise
ratio (PSNR), structural similarity index (SSIM), and the area under
50\%-iso-field contour overlap error. This error refers to the
computational reconstruction accuracy of the compressed sensing
algorithm when benchmarked against a densely sampled high-resolution
reference scan. Main results. Results demonstrated that accurate
field reconstruction can be achieved using only 8\% of the full
measurements, reducing acquisition time from 135 minutes to just 11
minutes, while maintaining clinically relevant precision (SSIM = 0.9,
PSNR = 27 dB, 50\%-iso-field contour overlap error is within ± 2.5\%). Significance.
In this way, the need for extensive measurements is reduced while
validation reliability is maintained. This approach delivers a faster
solution, enhancing information content while significantly reducing the
time required for quality assurance in hyperthermia clinics.
| Original language | English |
|---|---|
| Article number | 245022 |
| Number of pages | 10 |
| Journal | Physics in Medicine and Biology |
| Volume | 70 |
| Issue number | 24 |
| Early online date | 18 Dec 2025 |
| DOIs | |
| Publication status | Published - 21 Dec 2025 |
Keywords
- Phantom
- Medical robots and systems
- Radiofrequency
- Reconstruction algorithm
- Signal processing
- Electromagnetic Fields
- Humans
- Signal-To-Noise Ratio
- Hyperthermia, Induced/instrumentation
- Quality Assurance, Health Care
- Algorithms
- Phantoms, Imaging
- Quality Control
- electric field sensing
- hyperthermia
- compressed sensing
- quality assurance
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