IEEE Signal Processing - March 2018 - 167

overcome, rtUST could lead to quantitative thermometry with high sensitivity
and specificity with potential applications in noninvasive, nonionizing imaging inflammation-a grand challenge in
medical imaging.

heated region, i.e., spatially correlated
estimation errors. All of these remaining challenges are in the realm of signal
processing, requiring solutions ranging
from spatiotemporal model-based filters
to iterative reconstructive imaging. Once

US temperature sensitivity
The temperature dependence of the
speed of sound is well known and has
been extensively studied for decades.
More recently, based on a careful examination of the literature, Miller et al. [4]

Real-Time Thermography in Medicine
Nonionizing Imaging Modalities
The best-known example of thermography in medicine is
infrared imaging of the breast. This method was proposed in
the 1950s and gained U.S. Food and Drug Administration
approval in 1982. However, it has not been accepted either
as a screening tool in the detection of breast cancer or as an
adjunctive diagnostic tool. While this method reliably measures surface temperature, reconstructing the internal threedimensional temperature fields remains a major challenge.
Microwave radiometry is another method that has a great
appeal due to the fundamental nature of thermal noise, but it
has not gained acceptance in clinical applications due to
poor spatial and temporal resolutions.
Modern diagnostic imaging modalities such as magnetic
resonance (MR) and ultrasound (US) offer the promise of thermographic solutions with higher specificity than infrared
imaging and microwave radiometry. Today, MR thermography (MRT) and US thermography (UST) are the most widely
investigated modalities. Even within each modality, several
methods have been proposed, each exploiting the temperature sensitivity of one or more imaging parameters. For example, in MR imaging (MRI), the proton resonance frequency
(PRF) is a temperature-sensitive parameter due to the temperature dependence of the shielding constant v (i) . Furthermore,
v (i) ? i, which produces a linear temperature imaging
equation Di = (U (i) - U (i ref)) / (k p ·fref ·TE), where the PRF
shift (f (i) - fref) is interpreted as a phase shift. The values of v
for fat and water are ~1.3 # 10 -6 and ~4.5 # 10 -6,

respectively. The temperature dependence of the water proton
resonance is ~0.01 ppm/c C while the PRFs of lipid hydrogens are largely independent of temperature. Therefore, tissues with significant fat content present a challenge for this
method. In the absence of fat, this parameter is largely tissue
independent with the small dependency related to ion concentration. The spatial and temporal resolutions reported in
Table S1 for the PRF method were obtained with a standard
deviation of 1 1cC in immobile tissues. For all of the other
methods Table S1, the temperature imaging equations are
nonlinear and exhibit higher levels of tissue dependence.
MRT Versus UST
The PRF method stands out being largely tissue independent,
which is a key advantage. Furthermore, as with most MR parameters, the dependence is related to the molecular composition, which could lead to higher specificity. On the other hand,
all US-based methods exhibit high tissue dependence, which
limits their range to temperatures below 50 °C. Fortunately,
this still covers the majority of envisioned medical applications,
including imaging inflammation. The spatial resolution is comparable for both methods with UST holding a slight advantage. UST holds a clear advantage in terms temporal
resolution, especially with the advent of high frame rate US. Finally, MR continues to be expensive and requires MR compatibility (e.g., when using MRT for monitoring interventions).
These provide clear advantages for UST, which is inexpensive
and can be easily integrated with other medical devices.

Table S1. Examples of MR and US methods for thermography and thermometry.
Modality
MR

Method
PRF

Temperature Dependence
~ (i) = cB 0 (1 - v (i))

Tissue Dependence
Low

Sensitivity
~0.01 ppm/°C

Spatial
Resolution
O (mm)

Temporal
Resolution
O (1s)

MR

Spin-lattice relaxation

T1 ~e - (E a (T1) /ki)

High

1-2%/°C

O (mm)

O (1s)

MR

Water diffusion coefficient

D ~e - (E a (D) /ki)

Medium

~2%/°C

O (mm)

O (1s)

US

Mean scatterer resonance

f (i) = (c (i) /2d s (i))

High

~0.05%/°C

O (mm)

O (ms)

US

Echo shift

(5)

High

~0.05%/°C

O (mm)

O (ms)

US

Backscatter energy

(4)

High

0.3 dB/°C

O (1cm)

O (1s)

Parameters: c (gyromagnetic ratio), B 0 (static magnetic field), v (shielding constant), E a (activation energy), k (Boltzmann constant), c (speed of sound), and
d s (mean scatterer spacing).

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March 2018

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