Applying Magneto-Rheology to Reduce Blood Viscosity and Suppress Turbulence to Prevent Heart Attacks

Recently, Russ Hobbie pointed out to me an abstract presented at the 2017 American Physical Society March Meeting about “Applying Magneto-Rheology to Reduce Blood Viscosity and Suppress Turbulence to Prevent Heart Attacks," by Rongjia Tao.

Heart attacks are the leading causes of death in USA. Research indicates one common thread, high blood viscosity, linking all cardiovascular diseases. Turbulence in blood circulation makes different regions of the vasculature vulnerable to development of atherosclerotic plaque. Turbulence is also responsible for systolic ejection murmurs and places heavier workload on heart, a possible trigger of heart attacks. Presently, neither medicine nor method is available to suppress turbulence. The only method to reduce the blood viscosity is to take medicine, such as aspirin. However, using medicine to reduce the blood viscosity does not help suppressing turbulence. In fact, the turbulence gets worse as the Reynolds number goes up with the viscosity reduction by the medicine. Here we report our new discovery: application of a strong magnetic field to blood along its flow direction, red blood cells are polarized in the magnetic field and aggregated into short chains along the flow direction. The blood viscosity becomes anisotropic: Along the flow direction the viscosity is significantly reduced, but in the directions perpendicular to the flow the viscosity is considerably increased. In this way, the blood flow becomes laminar, turbulence is suppressed, the blood circulation is greatly improved, and the risk for heart attacks is reduced. While these effects are not permanent, they last for about 24 hours after one magnetic therapy treatment.

The report is related to an earlier paper by Tao and Ke Huang “Reducing Blood Viscosity with Magnetic Fields” (Phys Rev E, Volume 84, Article Number 011905, 2011). The APS published a news article about this work.

I have some concerns. Let’s use basic physics, like that discussed in Intermediate Physics for Medicine and Biology, to make order-of-magnitude estimates of the forces acting on a red blood cell.

First, we’ll estimate the dipole-dipole magnetic force. A red blood cell has a funny shape, but for our back-of-the-envelope calculations let’s consider it to be a cube 5 microns on a side. The magnetization M, the magnetic field intensity H, and the magnetic susceptibility χ_m are related by M = χ_m H (Eq. 8.31, all equation numbers from the 5th edition of IPMB), and H is related to the applied magnetic field B by B = μ_o H (Eq. 8.30), where μ_o is the permeability of free space. The total magnetic dipole of a red blood cell, m, is then a³M (Eq. 8.27), or m = a³χ_mB/μ_o. If we use χ_m = 10^-5, B = 1 T, and μ_o = 4π × 10^-7 T m/A, the dipole strength is about 10^-15 A m². The magnetic field produced by this magnetic dipole in an adjacent red blood cell is about μ_om/(4πa³) = 10^-6 T (Eq. 18.32). The force on a magnetic dipole in this nonuniform magnetic field is approximately mB/a = 2 × 10^-16 N (Eq. 8.26).

What other forces act on this red blood cell? Consider a cell in an arteriole that has a radius of 30 μm, is 10 mm long, and has a pressure drop from one end of the arteriole to the other of 45 torr = 6000 Pa (see Table 1.4 of IPMB). The pressure gradient dP/dx is therefore 6 × 10⁵ Pa/m. The pressure difference between one side of a red blood cell and the other should be the product of the pressure gradient and the cell length. The force is this pressure difference times the surface area, or a³dP/dx = 8 × 10^-11 N. This force is about 400,000 times larger than the magnetic force calculated above.

Another force arises from friction between the fluid and the cell. It is equal to the product of the surface area (a²), the viscosity η, and the velocity gradient (Eq. 1.33). Take the blood viscosity to be 3 × 10^-3 Pa s. If we assume Poiseuille flow, the average speed of the blood in the arteriole is 0.02 m/s (Eq. 1.37). The average velocity gradient should be the average speed divided by the radius, or about 700 1/s. The viscous force is then 5  × 10^-11 N. This is almost the same as the pressure force. (Had we done the calculation more accurately, we should have found the two forces have the same magnitude and cancel each other out, because the blood is not accelerating).

Another small force acting on the red blood cell is gravity. The gravitational force is the density times the volume times the acceleration of gravity (Eq. 1.31). If we assume a density of 1000 kg/m³, this force is equal to about 10^-12 N. Even if this overestimates the force of gravity by a factor of a thousand because of buoyancy, it is still nearly an order of magnitude larger than the magnetic force.

These back-of-the-envelope calculations suggest that the dipole-dipole force is very small compared to other forces acting on the red blood cell. It is not obvious how it could trigger cell aggregation.

Let me add a few other points.

• The abstract talks about suppressing turbulence. However, as Russ and I point out in IPMB, turbulence is only important in the largest vessels of the circulatory system, such as the aorta. In the vast majority of vessels there is no turbulence to suppress. 
• In their 2011 paper, Tao and Huang claim the change in viscosity is caused by aggregation of blood cells, and their Fig. 3c shows one such clump of about a dozen cells. However, capillaries are so small that blood cells go through them one at a time. Aggregates of cells might not be able to pass through a capillary. 
• If a magnetic field makes dramatic changes in blood viscosity, then you should experience noticeable changes in blood flow and blood pressure during magnetic resonance imaging, which can expose you to magnetic fields of several tesla. I have not seen any reports of such hemodynamic changes during an MRI. 
• I would expect that an aggregate of blood cells blocking a vessel could cause a stroke. I have never heard of an increased risk of stroke when a person is exposed to a magnetic field. 
• Tau and Huang claim that for the dipole interaction energy to be stronger than thermal energy, kT, the applied magnetic field should be on the order of 1 T. I have reproduced their calculation and they are correct, but I am not sure kT is the relevant energy for comparison. A 1 T magnetic field would result in a dipole-dipole interaction energy for the entire red blood cell of about kT. At the temperature of the human body kT is about 1/40 of an electron volt, which is less than the energy of one covalent bond. There are about 10¹⁴ atoms making up a red blood cell. Is one extra bond among those hundred million million atoms going to cause aggregation? 
• The change in viscosity apparently depends on direction. I can see how you could adjust the geometry so the magnetic field is parallel to the blood flow for one large artery or vein, but the arterioles, veinuoles, and especially capillaries are going to be oriented every which way. Blood flow is slower in these small vessels, so red blood cells spend a large fraction of their time in them. I expect that in some vessels the viscosity would go up, and in others it would go down. 
• Tao claims that the increase in viscosity lasts 24 hours after the magnetic field is turned off. If the dipole-dipole interaction causes this effect, why does it last so long after the magnetic field is gone? Perhaps the magnetic interaction pushes the cells together and then other chemical reactions cause them to stick to each other. But if that were the case, then why are the cells not sticking together whenever they bump into each other as they tumble through the circulatory system? 
• Finally--and this is a little out of my expertise so I am on shakier ground here--doctors recommend aspirin because of its effect on blot clotting, not because it reduces viscosity.

What lessons can we learn from this analysis? First, I am not convinced that this effect of magnetism on blood viscosity is real. I could be wrong, and I may be missing some key piece of the puzzle. I'm a simple man, and the process may be inherently complex. Nevertheless, it just doesn’t make sense to me. Second, you should always make back-of-the-envelope estimations of the effects you study. Russ and I encourage such estimates in Intermediate Physics for Medicine and Biology. Get into the habit of using order-of-magnitude calculations to check if your results are reasonable.

Free-Radical Chain Reactions that Spread Damage and Destruction

One way radiation damages tissue is by producing free radicals, also known as reactive oxygen species. In Chapter 16 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss these molecules:

High-LET [linear energy transfer] radiation produces so many ion pairs along its path that it exerts a direct action on the cellular DNA. Low-LET radiation can also ionize, but it usually acts indirectly. It ionizes water (primarily) according to the chemical reaction

H₂O → H₂O⁺ + e^- .

The H₂O⁺ ion decays with a lifetime of about 10^-10 s to the hydroxyl free radical:

H₂O⁺ + H₂O → H₃O⁺ + OH .

This then produces hydrogen peroxide and other free radicals that cause the damage by disrupting chemical bonds in the DNA.

Free radicals are produced not only by water, but also by oxygen, O₂. Tissues without much oxygen (such as the ischemic core of a tumor) are resistant to radiation damage.

Oxygen, by Nick Lane.

Nick Lane’s book Oxygen: The Molecule that Made the World explains how radiation interacts with tissue through free radicals. In his Chapter 6, “Treachery in the Air: Oxygen Poisoning and X-Irradiation: A Common Mechanism,” he writes:

A free radical is loosely defined as any molecule capable of independent existence that has an unpaired electron. This tends to be an unstable electronic configuration. An unstable molecule in search of stability is quick to react with other molecules. Many free radicals are, accordingly, very reactive…

The three intermediates formed by irradiating water, the hydroxyl radicals, hydrogen peroxide and superoxide radicals, react in very different ways. However, because all three are linked and can be formed from each other, they might be considered equally dangerous…

Hydroxyl radicals (^•OH) are the first to be formed. These are extremely reactive fragments, the molecular equivalents of random muggers. They can react with all biological molecules at speeds approaching their rate of diffusion. This means that they react with the first molecules in their path and it is virtually impossible to stop them from doing so. They cause damage even before leaving the barrel of the gun…

If radiation strips a second electron from water, the next fleeting intermediate is hydrogen peroxide (H₂O₂)…Hydrogen peroxide is unusual in that it lies chemically exactly half way between oxygen and water. This gives the molecule something of a split personality. Like a would-be reformed mugger, whose instinct is pitted against his judgement, it can go either way in its reactions….[A] dangerous and significant reaction, however, takes place in the presence of iron, which can pass electrons one at a time to hydrogen peroxide to generate free radicals. If dissolved iron is present, hydrogen peroxide is a real hazard…

The third of our intermediates … [is] the superoxide radical (O₂^•-). Like hydrogen peroxide, the superoxide radical is not terribly reactive. However, it too has an affinity for iron…

In summary, then, the three intermediates between water and oxygen operate as an insidious catalytic system that damages biological molecules in the presence of iron. Superoxide radicals release iron from storage depots and convert it into the soluble form. Hydrogen peroxide reacts with soluble iron to generate hydroxyl radicals. Hydroxyl radicals attack all proteins, lipids and DNA indiscriminately, initiating destructive free-redical chain reactions that spread damage and destruction.

I fear that physics and biology alone are not enough to understand how radiation interacts with tissue; we need some chemistry too.

Magnetic Force Microscopy for Nanoparticle Characterization

In Chapter 8 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss biomagnetism. The 5th edition of IPMB contains a brief new section on magnetic nanoparticles

8.8.4 Magnetic Nanoparticles

Small single-domain nanoparticles (10–70 nm in diameter) are used to treat cancer (Jordan et al. 1999; Pankhurst et al. 2009). The particles are injected into the body intravenously. Then an oscillating magnetic field is applied. It causes the particles to rotate, heating the surrounding tissue. Cancer cells are particularly sensitive to damage by hyperthermia. Often the surface of the nanoparticles can be coated with antibodies that cause the nanoparticle to be selectively taken up by the tumor, providing more localized heating of the cancer.

Suppose you wanted to image the distribution of nanoparticles in tissue. How would you do it? In IPMB we describe several ways to map magnetic field distributions, including using a superconducting quantum interference device (SQUID) magnetometer. Is there a way to get even better spatial resolution than using a SQUID? Gustavo Cordova, Brenda Yasie Lee, and Zoya Leonenko recently published a review in the NanoWorld Journal describing “Magnetic Force Microscopy for Nanoparticle Characterization” (Volume 2, Pages 10–14, 2016). Their abstract states

Since the invention of the atomic force microscope (AFM) in 1986, there has been a drive to apply this scanning probe technique or a form of this technique to various disciplines in nanoscale science. Magnetic force microscopy (MFM) is a member of a growing family of scanning probe methods and has been widely used for the study of magnetic materials. In MFM a magnetic probe is used to raster-scan the surface of the sample, of which its magnetic field interacts with the magnetic tip to offer insight into its magnetic properties. This review will focus on the use of MFM in relation to nanoparticle characterization, including superparamagnetic iron oxide nanoparticles, covering MFM imaging in air and in liquid environments.

Figure 1 from their paper shows how the MFM “two-pass technique” works: a first scan produces a topographical image using an atomic force microscope, and then a second pass creates a magnetic image using a magnetic force microscope. Both the AFM and MFM are based on using a small, nanometer sized scanning tip attached to a cantilever to detect small-scale tip deflections.

Their Figure 2 shows the results of MFM imaging of superparamagnetic iron oxide nanoparticles (SPIONs). The technique has sufficient sensitivity that they can measure how the size distribution of SPIONs depends on the particle coating.

Cordova et al. conclude

Considering rapid development of novel applications of magnetic nanoparticles in medicine and biomedical nanotechnology, as therapeutic agents, contrast agents in MRI imaging and drug delivery [3] MFM characterization of nanoparticles becomes more valuable and desirable. Overall, MFM has proven itself to be an effective yet underused tool that offers great potential for the localization and characterization of magnetic nanoparticles.

The magnetic force microscope does not have the exquisite picotesla sensitivity and millisecond time resolution of a SQUID, and it requires access to the tissue surface so you can scan over it. But for static, strong-field systems such as magnetic nanoparticle distributions, the magnetic force microscope provides exceptional spatial resolution, and represents one more tool in the physicists arsenal for imaging magnetic fields in biology.

The Thermodynamics of the Proton Spin

In Intermediate Physics for Medicine and Biology, Russ Hobbie and I introduce a lot of statistical mechanics and thermodynamics. For instance, in Chapter 3 we describe the Boltzmann factor and the heat capacity, and in Chapter 18 we analyze magnetic resonance imaging by considering the magnetization of the two-state spin system using statistical mechanics. Perhaps we can do a little more.

First, let’s calculate the average energy of a spin-1/2 proton in a magnetic field B. The proton has two states: up and down. Up has the lower energy E_up = -μB, and down has the higher energy E_down = +μB, where μ is the proton’s magnetic moment. Using the Boltzmann factor, the probability of having spin up is P_up = C e^μB/kT, and of spin down is P_down = C e^-μB/kT, where T is the absolute temperature and k is Boltzmann’s constant. The spin must be in one of these two states, so P_up + P_down = 1, or C = 1/(e^μB/kT + e^-μB/kT). The average energy, ⟨E⟩, is P_upE_up + P_downE_down, or

The total energy E of the spin system is just the average energy times the number of spins, E = N⟨E⟩.

Equations are not just things you plug numbers into to get other numbers. Equations tell a physical story. So, whenever I teach the two-state spin system I stress the story, which becomes clearer if we examine the limiting cases of this equation. At high temperatures (μB much less than kT), the argument of the hyperbolic tangent is small, we can use a Taylor expansion for the exponentials, and the average energy is –μ²B²/kT. This is the limit of interest for magnetic resonance imaging, when the average energy increases as the square of the magnetic field. At low temperatures (μB much greater than kT), the argument of the hyperbolic tangent is large, tanh goes to one, and the average energy is –μB. All the spins are in the spin up ground state.

Next, let’s calculate the heat capacity, C = dE/dT. The derivative of the hyperbolic tangent is the hyperbolic secant squared, so

The leading factor is the number of molecules time the Boltzmann constant, which is equal to the number of moles times the gas constant. At high temperatures, C goes to zero because of the leading factor of 1/T². Physically, this result arises because in this case the spins are approximately half spin up and half spin down, so the average energy is about zero, and making the system even hotter won’t change the situation. You typically see this type of behavior in systems that have an upper energy level (as opposed to, say, a system like the harmonic oscillator that has energy levels at increasing energies without bound). At low temperatures, C also goes to zero because the secant goes to zero at large argument. This result arises because the spin down state freezes out: if the system is cold enough no spins can reach the spin down state so the average energy is simply the energy of the spin up ground state.

The heat capacity going to zero as the temperature goes to zero is one way of stating the third law of thermodynamics. Russ and I discuss the first and second laws of thermodynamics in IPMB, but not the third. This is mainly because life occurs at warm temperatures, so the behavior as T approaches absolute zero does not have much biological significance. But although little biology happens around absolute zero, much physics does. To learn more about the world at low temperatures, I recommend the book The Quest for Absolute Zero, by Kurt Mendelssohn. Fascinating reading.

Erythropoietin and Feedback Loops

In Chapter 10 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss feedback loops. We included two new problems about feedback loops in the 5^th edition of IPMB, but as Russ says “you can never have too many examples.” So, here’s another.

The number of red blood cells is controlled by a feedback loop involving the hormone erythropoietin. The higher the erythropoietin concentration, the more red blood cells are produced and therefore the higher the hematocrit. However, the kidney adjusts the production of erythropoietin in response to hypoxia (caused in part by too few red blood cells). The lower the hematocrit the more erythropoietin produced. This new homework problem illustrates the feedback loop. It reinforces concepts from Chapter 10 on feedback and from Chapter 2 on the exponential function, and requires the student to analyze data (albeit made-up data) rather than merely manipulating equations. Warning: the physiological details of this feedback loop are more complicated than discussed in this idealized example.

Section 10.3

Problem 17 ½. Consider a negative feedback loop relating the concentration of red blood cells (the hematocrit, or HCT) to the concentration of the hormone erythropoietin (EPO). In an initial experiment, we infuse blood or plasma intravenously as needed to maintain a constant hematocrit, and measure the EPO concentration. The resulting data are

HCT	EPO
(%)	(mU/ml)
20	200
30	60.1
40	18.1
50	5.45
60	1.64

In a healthy person, the kidney adjusts the concentration of EPO in response to the oxygen concentration (controlled primarily by the hematocrit). In a second experiment, we suppress the kidney’s ability to produce EPO, control the concentration of EPO by infusing the drug intravenously, and measure the resulting hematocrit. We find

EPO	HCT
(mU/ml)	(%)
1	35.0
2	36.0
5	39.1
10	45.0
20	59.5

(a) Plot these results on semilog paper and determine an exponential equation describing each set of data.

(b) Draw a block diagram of the feedback loop, including accurate plots of the two relationships.

(c) Determine the set point (you may have to do this numerically).

(d) Calculate the open loop gain.

Biochemist Eugene Goldwasser first reported purification of erythropoietin when working at the University of Chicago in 1977. In his essay “Erythropoietin: A Somewhat Personal History” he writes about his ultimately successful attempt to isolate erythropoietin from urine samples.

Unfortunately the amounts of active urine concentrates available to us from the NIH source or our own collection were still too small to make significant progress, and it seemed as if purification and characterization of human epo might never be accomplished—that it might remain merely an intriguing biological curiosity. The prospect brightened considerably when Drs. M. Kawakita and T. Miyake instituted a very large-scale collection of urine from patients with aplastic anemia in Kumamato City, Japan. After some lengthy correspondence, Dr. Miyake arrived in Chicago on Christmas Day of 1975, carrying a package representing 2550 liters of urine [!] which he had concentrated using our first-step procedure. He and Charles Kung and I then proceeded systematically to work out a reliable purification method…we eventually obtained about 8 mg of pure human urinary epo .

You can learn more about Goldwasser and his career in his many obituaries, for instance here  and here. A more wide-ranging history of erythropoietin can be found here.

Unequal Anisotropy Ratios

In Chapter 7 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss the bidomain model, a mathematical description of the anisotropic electrical properties of cardiac tissue.

Anisotropy plays an important role in the bidomain model. To see why, consider a solution to Laplace’s equation in a monodomain—a two-dimensional sheet of homogeneous, anisotropic tissue with straight fibers. If the x direction is chosen to be along the fiber direction (the direction of greatest conductivity), then Laplace’s equation becomes

 Now define a new set of coordinates

and

 You can show that in these new coordinates Laplace’s equation becomes

We have removed the effect of anisotropy by rescaling distance in the direction perpendicular to the fibers. If you try a similar trick with the bidomain model … you can find a new coordinate system that removes the effect of anisotropy in either the intracellular space or the extracellular space, but in general you cannot find a coordinate system that removes the anisotropy in both spaces simultaneously (Roth 1992).

My 1992 paper (Journal of Mathematical Biology, Volume 30, Pages 633–646) contains one of my favorite figures, which illustrates the importance of bidomain anisotropy visually. It is equivalent to an old concept from mechanics called the simultaneous diagonalization of two quadratic forms.

Russ and I continue,

Only in the special case of equal anisotropy ratios (σ_ix/σ_iy = σ_ox/σ_oy ) will the equations simplify dramatically. But the anisotropy ratios in the heart are not equal. In the intracellular space the ratio of conductivities parallel and perpendicular to the fibers is about 10:1, while in the extracellular space this ratio is about 4:1 (Roth 1997). Anisotropy plays an essential role in the electrical behavior of the heart, especially during electrical stimulation.

My 1997 paper (IEEE Transactions on Biomedical Engineering, Volume 44, Pages 326–328), published 20 years ago this month, contains an estimate of the bidomain conductivities. After surveying much of the available experimental data, I found

• Intracellular Longitudinal Conductivity     σ_iL     0.2 S/m 
  
• Intracellular Transverse Conductivity        σ_iT     0.02 S/m
• Extracellular Longitudinal Conductivity    σ_eL    0.2 S/m 
• Extracellular Transverse Conductivity       σ_eT    0.08 S/m

This means that the ratio of the conductivity along the fibers to the conductivity across the fibers is 10:1 in the intracellular space, while only 5:2 in the extracellular space.

… Hold on. In IPMB, Russ and I said σ_eL:σ_eT = 4:1, but now I am saying σ_eL:σ_eT = 5:2. Drat! IPMB is wrong. Another entry for the errata…

The 1997 paper is highly cited: Google Scholar lists 178 citations. This perplexes me, because I have many papers that are more significant and innovative, but have far fewer citations. I guess usefulness can sometimes be as important as significance and innovation.

Radiopaedia

A screenshot of Radiopaedia.org.

Readers of Intermediate Physics for Medicine and Biology learn topics in medical physics from a physics point-of-view. Often, however, the discussion in IPMB doesn’t emphasize clinical applications. Where can you get more clinical information? Radiopaedia! Radiopaedia.org is a free online website with a large collection of radiology cases and reference articles.

To see what this site is like, I typed some terms into its search box. When I searched for MRI, I found articles about topics that Russ Hobbie and I present in Chapter 18 of IPMB, such as MRI pulse sequences and MRI artifacts, but also a wealth of clinical topics such as protocols for MRI brain screens, stroke, demyelination, and rectal cancer. The site also contains many case studies of specific patients. And it doesn’t cost a thing.

Radiopaedia has much information about nuclear medicine (Chapter 17 in IPMB). I typed “^99mTc” into the search box and found articles describing a variety of radiopharmaceuticals based on the technetium-99m radioisotope. Also, the site has much information about positron emission tomography (PET) and single photon emission computed tomography (SPECT).

Radiopaedia covers the interaction of x-rays with tissue (Chapter 15 in IPMB) in a variety of articles about different mechanisms such as the photoelectric effect, Compton scattering, and pair-production. Many features of x-ray technology are also discussed (Chapter 16 in IPMB), like x-ray tubes, filters, collimators, grids, and intensifying screens. But also describes x-ray images of specific body parts, such as the abdomen, pelvis, ankle, and shoulder. And all this information is available gratis.

The web site discusses computed tomography qualitatively, but not quantitatively, and lacks much of the mathematics presented in Chapter 12 of IPMB. It contains many medical images, but almost no other figures. For example, the discussion of four generations of CT scanners would benefit from a figure, like Fig. 16.25 in IPMB.

Ultrasound is covered in Chapter 13 of IPMB, and also in Radiopaedia. Topics include transducers, pulse-echo imaging, elastography, and Doppler imaging. Best of all, this valuable information is on the house.

One of the best parts of Radiopaedia is the quiz mode for patient cases. You get to be the doctor, analyzing different medical problems. These cases are too difficult for me to diagnose, but perhaps you can. I find Radiopaedia to be a helpful, no-cost supplement to our book: IPMB supplies the math and physics, while Radiopaedia analyzes the clinical applications.

Did I mention that Radiopaedia is free?

Enjoy.

Top Ten Illustrations in Intermediate Physics for Medicine and Biology

I always love top ten lists, so I prepared a list of my top ten illustrations in Intermediate Physics for Medicine and Biology. These are a subjective, personal selections; you may prefer others. I excluded any figure that was reproduced in IPMB from another publication, so many of my favorite images are not listed. Except as noted, Russ Hobbie created these figures, and they appeared first in earlier editions of IPMB on which he was sole author.

10. Figure 15.30. Although this figure is not the most attractive of those in the top ten, I selected it because it is based on Russ’s simulation program MacDose. Be sure to watch Russ’s video based on MacDose; it is a great learning experience.

9. Figure 7.13. I helped create this figure when I was in graduate school. Russ asked my PhD advisor John Wikswo if he could supply two figures showing the extracellular potential (Fig. 7.13) and magnetic field (Fig. 8.14) produced by an axon. Wikswo asked me to do the calculations, and he had an illustrator in the lab produce the final drawing.

8. Figure 17.19.  This scintillation camera bone scan of a 7-year-old boy is spooky, with ghostly radioactive hot spots. It is one of the many medical images Russ obtained from colleagues at the University of Minnesota. In this case, Bruce Hallelquist provided the photo. IPMB is much the richer for all the images provided by Russ’s friends.

7. Figure 15.15. This figures illustrates the transfer of energy between photons and electrons. I like how it summarizes much of the chapter about the Interaction of Photons and Charged Particles with Matter in a single drawing.

6. Figure 14.24. New in the 4th edition of IPMB, this figure illustrates the blackbody radiation spectrum. It clarifies why the spectrum appears different when plotted versus frequency compared to when plotted versus wavelength.

5. Figure 12.12. This illustration defining the projection is critical to understanding tomography. Russ and I liked it so much that we considered using it on the cover of the 4th edition of IPMB, until Springer decided to go with their own cover design that didn’t include a figure from the book.

4. Figure 16.23. This image, obtained using digital subtraction angiography, is another medical illustration provided by one of Russ’s colleagues at the University of Minnesota (Richard Geise). I chose it because it is stunningly beautiful.

3. Figure 14.16. Color! This optical coherence tomogram of the retina was supplied by Kirk Morgan. A few figures in IPMB go beyond black and white, but this is the only one in glorious full color.

2. Figure 12.6. I like this magnetic resonance image of the brain because it helps build insight into how an image and its Fourier transform are related. It is the first of a series of six images in Chapter 12 prepared by Tuong Huu Le (University of Minnesota, also thanks to Xiaoping Hu) that, by themselves, provide a short course in image processing.

And the winner is….

1. Figure 7.16. This picture of the direction of the dipole during the cardiac cycle nicely summarizes the electrocardiogram. My career has focused on the bioelectric behavior of the heart, so it is fitting that my top pick builds on that theme. The reason I chose it, however, is because it was on the cover of the first edition of IPMB, which I used in my first medical physics course taught by John Wikswo at Vanderbilt University.

Enhancement of Human Color Vision by Breaking the Binocular Redundancy

Russ Hobbie and I added a discussion of color vision to the 5th edition of Intermediate Physics for Medicine and Biology.

The eye can detect color because there are three types of cones in the retina, each of which responds to a different wavelength of light (trichromate vision): red, green, and blue, the primary colors. However, the response curve for each type of cone is broad, and there is overlap between them (particularly the green and red cones). The eye responds to yellow light by activating both the red and green cones. Exactly the same response occurs if the eye sees a mixture of red and green light. Thus, we can say that red plus green equals yellow. Similarly, the color cyan corresponds to activation of both the green and blue cones, caused either by a monochromatic beam of cyan light or a mixture of green and blue light. The eye perceives the color magenta when the red and blue cones are activated but the green is not. Interestingly, no single wavelength of light can do this, so there is no such thing as a monochromatic beam of magenta light; it can only be produced my mixing red and blue. Mixing all three colors, red and green and blue, gives white light.

I know that some animals have dichromate vision (only two color receptors), as do some color blind people. Also, a few animals have tetrachromate vision (four color receptors). But I never imagined that I could have enhanced color vision just by wearing a pair of fancy glasses. Could I become a tetrachromat?

Yes! A preprint appeared recently in the biological physics arXiv by Mikhail Kats and his colleagues at the University of Wisconsin about “Enhancement of Human Color Vision by Breaking the Binocular Redundancy” (arXiv:1703.04392). Graduate student and National Science Foundation Graduate Research Fellow Brad Gundlach is the lead author of this fascinating paper. The abstract is given below.

To see color, the human visual system combines the responses of three types of cone cells in the retina—a process that discards a significant amount of spectral information. We present an approach that can enhance human color vision by breaking the inherent redundancy in binocular vision, providing different spectral content to each eye. Using a psychophysical color model and thin-film optimization, we designed a wearable passive multispectral device that uses two distinct transmission filters, one for each eye, to enhance the user’s ability to perceive spectral information. We fabricated and tested a design that “splits” the response of the short-wavelength cone of individuals with typical trichromatic vision, effectively simulating the presence of four distinct cone types between the two eyes (“tetrachromacy”). Users of this device were able to differentiate metamers (distinct spectra that resolve to the same perceived color in typical observers) without apparent adverse effects to vision. The increase in the number of effective cones from the typical three reduces the number of possible metamers that can be encountered, enhancing the ability to discriminate objects based on their emission, reflection, or transmission spectra. This technique represents a significant enhancement of the spectral perception of typical humans, and may have applications ranging from camouflage detection and anti-counterfeiting to art and data visualization.

I’d love to try out a pair of these glasses! I wonder whether they provide merely a subtle change in vision or offer an entirely new visual experience? Also, what would it be like to have each eye receiving different color information? Does the brain need to be trained to handle the additional information, or does it adapt easily? If the enhancement of vision is dramatic, I could easily see these glasses becoming the hot new gadget people clamor for this Christmas. And it all comes from applying physics to medicine and biology.

Five Popular Misconceptions about Osmosis

In Chapter 5 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss osmotic pressure.

5.2 Osmotic Pressure in an Ideal Gas

The selective permeability of a membrane gives rise to some striking effects. The flow of water that occurs because solutes are present that cannot get through the membrane is called osmosis. This phenomenon seems strange when it is first encountered, and explanations are often fraught with misconceptions (Kramer and Myers 2012).

What are these misconceptions that explanations are often fraught with? The reference is to the paper “Five Popular Misconceptions About Osmosis” (American Journal of Physics, Volume 80, Pages 694–699, 2012). The paper raises five questions.

1. Is osmosis limited to mixtures in the liquid state? 
2. Does osmosis require an attractive interaction between solute and solvent? 
3. Can osmosis drive solvent from a compartment of lower to higher solvent concentration? 
4. Can the osmotic pressure be interpreted as the partial pressure of the solute? 
5. What exerts the force that drives solvent across the semipermeable membrane, overcoming both viscous resistance and an opposing hydrostatic pressure gradient?

Later in the paper, the authors answer these questions.

1. The phenomenology of osmosis is the same for gases, liquids, and supercritical fluids. The misconception is that osmosis is limited to liquids. 
2. Osmosis does not depend on an attractive force between solute and solvent. The misconception is that osmosis requires an attractive force. 
3. Osmosis can drive solvent from a lower to a higher solvent concentration compartment. The misconception is that osmosis always happens down a concentration gradient. 
4. The osmotic pressure cannot be interpreted as the partial pressure of the solute. The misconception is that it can. 
5. The semipermeable membrane exerts the force that drives solvent flow. The misconception is that no force is required to explain the flow.

So, how did Russ and I do?

1. We certainly get the first question correct, because our initial explanation is for an ideal gas. 
2. I think we get the second one right too, but it is not as clear, because we restrict our discussion to ideal solutions in which no heat is evolved or absorbed. 
3. We cast our discussion in terms of the chemical potential, and then relate the chemical potential to the hydrostatic pressure and the solute concentration. I don’t think we ever address the issue of solvent concentration. I’ll say we are silent on this one. 
4. We say “Except in an ideal gas, it [the chemical potential] is not the same as the partial pressure (a concept that is not normally used in a liquid).” So we get this one right, and I’m glad we put the not in italics. 
5. In Section 5.9.6 we have a nice discussion about the forces acting on the membrane. But we never really say what force explains the solvent flow. Again, I’ll say we are silent on this one.

Kramer and Myers have an illuminating discussion about the force causing the solvent to cross the membrane (I’ve removed all their references; you can find them in the original paper).

Consider an idealized semipermeable membrane as a force field that repels solute but has no effect on the solvent. The Brownian motion of the solute molecules bring them into occasional contact with this field, at which time they receive some momentum directed away from the membrane. Viscous interactions between solute and solvent then rapidly distribute this momentum to the solvent molecules in the neighborhood of the membrane. In this way, the membrane exerts a repulsive force on the solution as a whole. Since additional pure solvent can freely cross our idealized membrane, it flows into the solution compartment, gradually increasing the hydrostatic pressure in the solution. Thus, a pressure gradient builds up across the thickness of the membrane. This pressure gradient exerts a second force on the solution, capable of counteracting the membrane force. Quantitative treatments show that the pressure difference required to stop solvent flow into a dilute solution is exactly Π = k_BTc_B. Nelson has aptly called the mechanism by which the membrane drives fluid flow the rectification of Brownian motion.

Overall I would say Russ and I do okay. We don’t propagate any of the five misconceptions. We answer three of their questions correctly and are silent on two others. Most of the discussion about osmosis goes back to the 3^rd or earlier editions of IPMB, so Russ is the one who got it right. At least I didn’t screw it up.

My Honors College Class: The Making of the Atomic Bomb

The Making of the Atomic Bomb,
by Richard Rhodes.

This semester I am teaching a class in Oakland University’s Honors College called “The Making of the Atomic Bomb,” based on Richard Rhodes’s book by the same name. The class is a mixture of nuclear physics, a history of the Manhattan Project, and a discussion about World War II (today we discuss Pearl Harbor). I became interested in this topic from the writings of Cameron Reed of Alma College here in Michigan.

The Honors College students are outstanding, but they are from disciplines throughout the university and do not necessarily have strong math and science backgrounds. Therefore the mathematics in this class is minimal, but nevertheless we do a two or three quantitative examples. For instance, Chadwick’s discovery of the neutron in 1932 was based on conclusions drawn from collisions of particles, and relies primarily on conservation of energy and momentum. When we analyze Chadwick’s experiment in my Honors College class, we consider the head-on collision of two particles of mass M₁ and M₂. Before the collision, the incoming particle M₁ has kinetic energy T and the target particle M₂ is at rest. After the collision, M₁ has kinetic energy T₁ and M₂ has kinetic energy T₂.

Intermediate Physics for Medicine and Biology examines an identical situation in Section 15.11 on Charged-Particle Stopping Power.

The maximum possible energy transfer W_max can be calculated using conservation of energy and momentum. For a collision of a projectile of mass M₁ and kinetic energy T with a target particle of mass M₂ which is initially at rest, a nonrelativistic calculation gives

One important skill I teach my Honors College students is how to extract a physical story from a mathematical expression. One way to begin is to introduce some dimensionless parameters. Let t be the ratio of kinetic energy picked up by M₂ after the collision to the incoming kinetic energy T, so t = T₂/T or, using the notation in IPMB, t = W_max/T (the subscript “max” arises because this maximum value of T₂ corresponds to a head-on collision; a glancing blow will result in a smaller T₂). Also, let m be the ratio of M₁ to M₂, so m = M₁/M₂. A little algebra results in the simpler-looking equation

The goal is to unmask the physical behavior hidden in this equation. The best way to proceed is to examine limiting cases. There are three that are of particular interest.

m much less than 1. When m is small (think of a fast-moving proton colliding with a stationary lead nucleus) the denominator is approximately one, so t = 4m. Because m is small, so is t. This means the proton merely bounces back elastically as if striking a brick wall. Little energy is transferred to the lead nucleus.

 m much greater than 1. When m is large (think of a fast-moving lead nucleus smashing into a stationary proton) the denominator is approximately m², so t = 4/m. Because m is large, t is small. This means the lead continues on as if the proton were not even there, with little loss of energy. The proton flies off at a high speed, but because of its small mass it carries off negligible energy.

m equal to 1. When m is one (think of a neutron colliding with a proton, which was the situation examined by Chadwick), the denominator becomes 4, and t = 1. All of the energy of the neutron is transferred to the proton. The neutron stops and the proton flies off at the same speed the neutron flew in.

A mantra I emphasize to my students is that equations are not just things you put numbers into to get other numbers. Equations tell a physical story. Being able to extract this story from an equation is one of the most important abilities a student must learn. Never pass up a chance to reinforce this skill.

Glucose, Mannitol, Sucrose, and Raffinose

The structure of glucose.

You would think by now I would know everything in Introductory Physics for Medicine and Biology; after all, I’m one of the authors. So when thumbing through the book the other day (doesn’t everyone thumb through IPMB when they have a spare moment?) I came across Figure 4.11, showing a log-log plot of the diffusion constant as a function of molecular radius. Four data points stand out—glucose, mannitol, sucrose, and raffinose—because they are plotted as open rather than solid circles. This figure was drawn originally by Russ Hobbie and has appeared in every edition of IPMB. I got to wondering “why did Russ choose to plot those four molecules out of the thousands available?” And then, more specifically, I found myself asking “just what is raffinose anyways?”

To figure all this out, I grabbed the textbook I read in graduate school while auditing the biochemistry class taken by Vanderbilt medical students (Biochemistry, by the late Geoffrey Zubay). These molecules are carbohydrates or, more simply, sugars. Glucose is the canonical example; this six-carbon molecule C₆H₁₂O₆ is “the single most important substrate for energy metabolism” and in humans it is “the single most important sugar in the blood”. It usually exists in a ring conformation. It is a monosaccharide because it consists of a single ring. Other monosaccharides are fructose and galactose, which all have the same formula, C₆H₁₂O₆, but the arrangement of the atoms is slightly different.

Mannitol differs from glucose by having an extra two hydrogen atoms: C₆H₁₄O₆. Technically it’s a sugar alcohol rather than a sugar. You’d think it would act similarly to glucose, but it doesn’t. Mannitol is relatively inert in humans. It doesn’t cross the blood-brain barrier (I discussed the implications of this previously in this blog) and it is not reabsorbed by the kidney like glucose is so it acts as an osmotic diuretic. In Fig. 4.11, the mannitol and glucose data almost overlap, and it is hard to tell which data point is which. According to a paper by Bashkatov et al. (2003), glucose has a larger diffusion coefficient than mannitol, so glucose must be the data point above and to the left, and mannitol below and to the right.

Sucrose is a disaccharide, which means it is two monosaccharides bound together through a “glycosidic linkage”. It’s common table sugar, and consists of a molecule of glucose bound to a molecule of fructose. Russ probably chose to plot sucrose as a typical disaccharide. Two other  disaccharides he could have chosen are lactose (glucose + galactose) and maltose (glucose + glucose).

Raffinose is a trisaccharide, consisting of galactose + glucose + fructose. Therefore, Russ’s choice of plotting glucose, sucrose, and raffinose makes sense: the most important monosaccharide, disaccharide, and trisaccharide. A fun fact about raffinose is that the human digestive tract does not have the enzyme needed to digest it. However, certain gas-producing bacteria in our gut can digest it, resulting in flatulence. You probably won’t be surprised to learn that beans often contain a lot of raffinose.

So, Russ is a clever fellow. He hid a short review of carbohydrate biochemistry in Fig. 4.11. Who knew?

Benefits and Barriers of Accommodating Intraocular Lenses

In Chapter 14 of Intermediate Physics for Medicine and Biology, Russ Hobbie and I discuss vision. In particular, we analyze the refraction of light by the lens of the eye, and examine different disorders such as hyperopia, and myopia. We then write

This ability of the lens to change shape and provide additional converging power is called accommodation…. As we age, the accommodation of the eye decreases... A normal viewing distance of 25 cm or less requires 4 diopters or more of accommodation... This limit is usually reached in the early 40s. To make up for the lack of accommodation, one can place a converging lens in front of the eye when viewing nearby objects (reading glasses).

When a patient has a cataract, their lens becomes cloudy. A common surgical procedure is to remove the opaque lens and replace it with an artificial intraocular lens. A conventional IOL is designed to supply the correct power to provide clear distance vision, but it cannot accommodate. Reading glasses provide one option for close vision, but many patients find them to be an inconvenient nuisance.

Researchers are now racing to create accommodating IOLs. A recent review by Jay Pepose, Joshua Burke, and Mujtaba Qazi discusses the “Benefits and Barriers of Accommodating Intraocular Lenses” (Current Opinion in Ophthalmology, Volume 28, Pages 3–8, 2017).

Presbyopia [the loss of accommodation] and cataract development are changes that ubiquitously affect the aging population. Considerable effort has been made in the development of intraocular lenses (IOLs) that allow correction of presbyopia postoperatively. The purpose of this review is to examine the benefits and barriers of accommodating IOLs, with a focus on emerging technologies.

Apparently the current accommodating intraocular lenses don’t function by changing their focal length, but rather by being pushed forward when the eye muscles responsible for accommodation contract. They only provide about 1 diopter of accommodation, which is not enough to avoid reading glasses. The review concludes

Such limitations [of the presently available accommodating IOLs] may be circumvented in the future by accommodative design strategies that rely more on shape-related changes in the surfaces of the IOLs or in refractive index than by forward translation alone. Fibrosis and contraction of the capsular bag, which can alter the position of the IOL optic or the performance of an accommodating IOL represent other challenges, and at least one accommodating IOL … has been designed for implantation in the ciliary sulcus. Approval of accommodating IOLs capable of delivering three or more diopters of accommodation would allow a full range of intermediate and near vision without the compromise of photic phenomenon or loss of contrast inherent to other optical strategies, and perhaps also allow refractive targeting that could minimize hyperopic surprises by taking advantage of this expanded amplitude of accommodation.

Some “accommodating” IOLs are multifocal, providing two focal lengths and therefore two images simultaneously, one for distance vision and one for reading. The brain then sorts out the mess. Apparently this is not as difficult as is sounds.

I predict that accommodating intraocular lenses will soon become very sophisticated. Cataract surgery is performed on millions of people each year; it is common in the elderly population, which is growing dramatically as baby boomers age; in principle the problem is not complex, you just need to make a lens that can adjust its focal length by about ten percent; compared to other medical devices like pacemakers and defibrillators, accommodating IOLs should be cheap; and new nanotechnologies plus knowledge gained from the miniaturization of other medical devices may pave the way to rapid advances. Accommodating intraocular lenses may soon become an example of how to successfully apply physics to solve a problem in medicine.

Sir Peter Mansfield (1933-2017)

MRI pioneer Peter Mansfield died last week. Russ Hobbie and I mention Mansfield in Chapter 18 of Intermediate Physics for Medicine and Biology

Many more techniques are available for imaging with magnetic resonance than for x-ray computed tomography. They are described by Brown et al. (1994), by Cho et al. (1993), by Vlaardingerbroek and den Boer (2004), and by Liang and Lauterbur (2000). One of these authors, Paul C. Lauterbur, shared with Sir Peter Mansfield the 2003 Nobel Prize in physiology or medicine for the invention of magnetic resonance imaging.

Mansfield made many contributions to the development of MRI, including the invention of echo-planar imaging. Russ and I write

Echo-planar imaging (EPI) eliminates the π pulses [normally used to rotate the spins in the x-y plane to form a spin echo]. It requires a magnet with a very uniform magnetic field, so that T₂ [the transverse relaxation time, that is determined in part by dephasing of the spins in the x-y plane] (in the absence of a gradient) is only slightly greater than T₂^* [the experimentally observed transverse relaxation time]. The gradient fields are larger, and the gradient pulse durations shorter, than in conventional imaging. The goal is to complete all the k-space [all the points k_x-k_y in the spatial frequency domain] measurements in a time comparable to T₂^*. In EPI the echoes are not created using π pulses. Instead, they are created by dephasing the spins at different positions along the x axis using a G_x gradient, and then reversing that gradient to rephrase the spins, as shown in Fig. 18.32.

A MRI pulse sequence for echo planar imaging,
from Intermediate Physics for Medicine and Biology.

Mansfield tells about his first presentation on echo-planar imaging in his autobiography, The Long Road to Stockholm.

It was during the course of 1976 that Raymond Andrew convened a meeting in Nottingham of interested people in imaging…Most attendees brought us up to date with their images and gave us short talks on the goals that they were pursuing. Although my group had made considerable headway in a whole range of topics, I chose to speak about an entirely new imaging method that I had worked out theoretically but for which I had really no experimental results. The technique was called echo planar imaging (EPI), a condensation of planar imaging using spin echoes. I spoke for something like half an hour, talking in great detail, and at the end of the talk the audience seemed to be left in stunned silence. There were no questions, there was no discussion at all, and it was almost as though I had never spoken. In fact I had given a detailed talk about how one could produce very rapid images in a typically one shot process lasting, conservatively, for something like 40 or 50 milliseconds.

You can learn more about Mansfield in obituaries in the New York Times, in The Scientist, and from the BBC. Also, the Nobel Prize website has much information including a biography and his Nobel Prize address. Below, watch and listen to Mansfield talk about MRI.