Friday, September 28, 2012

Benedek and Villars, Volume 3

Physics With Illustrative Examples  From Medicine and Biology, Volume 3,  by Benedek and Villars, superimposed on Intermediate Physics for Medicine and Biology.
Physics With Illustrative Examples
From Medicine and Biology, Volume 3,
by Benedek and Villars.
This is the third and final entry in a series of blog entries about Benedek and Villars’ textbook Physics With Illustrative Examples From Medicine and Biology. Today I discuss Volume 3, about electricity and magnetism. In the preface to the first edition of Volume 3, Benedek and Villars write
With this volume on Electricity and Magnetism, we complete the third and final volume of our textbooks on Physics, with Illustrative Examples from Medicine and Biology. We believe that this volume is as unique as our previous books on Classical Mechanics (Vol. 1) and Statistical Physics (Vol. 2). Here, we continue our program of interweaving into the rigorous development of classical physics, an analysis and clarification of a wide variety of important phenomena in physical chemistry, biology, physiology, and medicine.
All three volumes of Physics With Illustrative Examples From Medicine and Biology, by Benedek and Villars, superimposed on Intermediate Physics for Medicine and Biology.
All three volumes of
Physics With Illustrative Examples
From Medicine and Biology,
by Benedek and Villars.
The topics covered in Volume 3 are similar to those Russ Hobbie and I discuss in Chapters 6-9 in the 4th edition of Intermediate Physics for Medicine and Biology. Because I do research in the fields of bioelectricity and biomagnetism, you might expect that this would be my favorite volume of the three, but it’s not. I don’t find that it contains as many rich and interesting biological examples. Yet it is a solid book, and contains much useful electricity and magnetism.

All three volumes of Physics With Illustrative Examples From Medicine and Biology, by Benedek and Villars, with Intermediate Physics for Medicine and Biology.
Physics With Illustrative Examples
From Medicine and Biology,
by Benedek and Villars.
Before leaving this topic, I should say a few words about George Benedek and Felix Villars. Benedek is currently the Alfred H. Caspary Professor of Physics and Biological Physics in the Department of Physics in the Harvard-MIT Division of Health Sciences and Technology. His group’s research program “centers on phase transitions, self-assembly and aggregation of biological molecules. These phenomena are of biological and medical interest because phase separation, self-assembly and aggregation of biological molecules are known to play a central role in several human diseases such as cataract, Alzheimer's disease, and cholesterol gallstone formation.” Villars was born in Switzerland. In the late 1940s, he collaborated with Wolfgang Pauli, and developed Pauli-Villars regularization. He began work at the MIT in 1950, where he collaborated with Herman Feshbach and Victor Weisskopf. He became interested in the applications of physics to biology and medicine, and helped establish the Harvard-MIT Division of Health Sciences and Technology. He died in 2002 at the age of 81.

Friday, September 21, 2012

Benedek and Villars, Volume 2

Physics With Illustrative Examples  From Medicine and Biology, Volume 2,  by Benedek and Villars, superimposed on Intermediate Physics for Medicine and Biology.
Physics With Illustrative Examples
From Medicine and Biology, Volume 2,
by Benedek and Villars.
Last week I discussed volume 1 of Benedek and Villars’ three-volume textbook Physics With Illustrative Examples From Medicine and Biology, which dealt with mechanics. The second volume discusses statistical physics. The preface to their first edition of Volume 2 states
In the present volume we develop and present the ideas of statistical physics, of which statistical mechanics and thermodynamics are but one part. We seek to demonstrate to students, early in their career, the power, the broad range, and the astonishing usefulness of a probabilistic, non-deterministic view of the origin of a wide range of physical phenomena. By applying this approach analytically and quantitatively to problems such as: the size of random coil polymers; the diffusive flow of solutes across permeable membranes; the survival of bacteria after viral attack; the attachment of oxygen to the binding sites on the hemoglobin molecule; and the effect of solutes on the boiling point and vapor pressure of volatile solvents; we demonstrate that the probabilistic analysis of statistical physics provides a satisfying understanding of important phenomena in fields as diverse as physics, biology, medicine, physiology, and physical chemistry.
Many of the topics in Volume 2 of Benedek and Villars are similar to Chapters 3–5 in the 4th edition of Intermediate Physics for Medicine and Biology: the Boltzmann factor, diffusion, and osmotic pressure. As I said last week, I’m most interested in those topics Benedek and Villars discuss that are not covered in Intermediate Physics for Medicine and Biology, such as their fascinating description of the use of Poisson statistics by Luria and Delbruck.
If a bacterial culture is brought into contact with bacteriophage virus particles, the viruses will attack the bacteria and kill them in a matter of hours. However, a small number of bacteria do survive the attack. These survivors will reproduce and pass on to their descendants their resistance to the virus. The form of resistance of the offspring of the surviving bacteria is that their surface does not adsorb the attacking virus. Bacterial strains can also be resistant to metabolic inhibitors, such as streptomycin, penicillin, and sulphonamide. If a bacterial culture is subjected to attack by these antibiotics, the resistant strain will emerge just as in the case of the phage resistant bacteria.

In the early 1940s, Luria and Delbruck were working on ‘mixed infection’ experiments in which the bacteriophage resistant strain of E. coli bacteria were used as indicators in studies they were making on T1 and T2 virus particles. Starting in the Fall of 1942, they began to put aside the mixed infection experiment and asked themselves: What is the origin of those resistant bacterial strains that they were using as indicators?
They go on to give a detailed description of how Poisson statistics were used by Luria and Delbruck to study mutations.

Russ Hobbie and I discuss the Poisson distribution in our Appendix J. The Poisson distribution is an approximation of the more familiar binomial distribution, applicable for large numbers and small probabilities. One can see how this distribution would be appropriate for Luria and Delbruick, who had large numbers of viruses and a small probability of a mutation.

Russ and I cite Volume 1 of Benedek and Villars’ text in our Chapter 1 on biomechanics. We draw the data for our Fig. 4.12 from Benedek and Villars’ Volume 2. We never cite their Volume 3, about electricity and magnetism, which I’ll discuss next week.

Friday, September 14, 2012

Benedek and Villars, Volume 1

Physics With Illustrative Examples  From Medicine and Biology, Volume 1,  by Benedek and Villars, superimposed on Intermediate Physics for Medicine and Biology.
Physics With Illustrative Examples
From Medicine and Biology, Volume 1,
by Benedek and Villars.
One early textbook that served as a precursor to Introductory Physics for Medicine and Biology is the 3-volume Physics With Illustrative Examples From Medicine and Biology, by George Benedek and Felix Villars. The first edition, published in 1973, was just bound photocopies of a typewritten manuscript, but a nicely printed second edition appeared in 2000. The preface to Volume 1 of the first edition states
This is a unique book. It is an introductory textbook of physics in which the development of the principles of physics is interwoven with the quantitative analysis of a wide range of biological and medical phenomena. Conversely, the biological and medical examples serve to vitalize and motivate the learning of physics. By its very nature, this book not only teaches physics, but also exposes the student to topics in fields such as anatomy, orthodedic medicine, physiology, and the principles of hemostatic control.

This book, and its follow-up, Volumes II and III, grew out of an introductory physics course which we have offered to freshmen and sophomores at MIT since 1970. The stimulus for this course came from Professor Irving M. London, MD, Director of the Harvard-MIT Program in Health Sciences and Technology. He convinced us that continued advances in the biological and medical sciences demand that students, researchers, and physicians should be capable of applying the quantitative methods of the physical sciences to problems in the life sciences. We have written this book in the hope that students of the life sciences will come to appreciate the value of training in physics in helping them to formulate, analyze, and solve problems in their own fields.
This quote applies almost without change (except for replacing MIT with Russ Hobbie’s University of Minnesota) to Intermediate Physics for Medicine and Biology. Clearly the goals and objectives of the two works are the same.

Many of the topics in Volume 1 of Benedek and Villars are similar to those found in Chapters 1 and 10 of Intermediate Physics for Medicine and Biology: biomechanics, fluid dynamics, and feedback. Particularly interesting to me are the topics that Russ Hobbie and I don’t discuss, such as the physiological effects of underwater diving.
On ascent and descent the diver must arrange to have the pressure of gas in his lungs be the same as that of the surrounding water. He can do this either by breathing out on ascent or by adjusting the output pressure of his compressed air tanks. Second to drowning, the most serious underwater diving accident is produced by taking a full breath of air at depth, and holding this breath as the diver rises to the surface quickly. For example, if the diver did this at 99 ft he would have gas at 4 atm in his lungs. This if fine at 99 ft, but if he holds this total volume of gas on ascending, then at the surface the surrounding water is at 1 atm, and his lungs are holding air at 3 atm. This can do two things. His lungs can rupture, thereby allowing gas to flow into the space between lungs and ribs. This is called pneumothorax. Also the great pressure of air in the lungs can force air bubbles into the blood stream. These air embolisms can then occlude blood vessels in the brain or the coronary circulation, and this can lead to death. Of course, the obvious necessity of balancing pressure in the ears, sinuses, and intestines must be realized.
Benedek and Villars also have a delightful description of the physiological effects of low air pressure experienced by balloonists. It is too long to reproduce here, but well worth reading.

In the coming weeks, I will discuss Benedek and Villars’ second and third volumes.

Friday, September 7, 2012

Are Backscatter x-ray machines at airports safe?

Two competing devices are used in airports to obtain full-body images of passengers: backscatter x-ray scanners and millimeter wave scanners. Today I want to examine those scanners that use x-rays.

Backscatter x-ray scanners work by a different mechanism than ordinary x-ray images used in medicine. Chapter 16 of the 4th edition of Intermediate Physics for Medicine and Biology discusses traditional medical imaging (see Fig. 16.14). X-rays are passed through the body, and the attenuation of the beam provides the signal that produces the image. Backscatter x-ray scanners are different. They record the x-rays scattered backwards toward the incident beam via Compton scattering. This allows the use of very weak x-ray beams, resulting in a lower dose.

The dose (or, more accurately the equivalent dose) from one backscatter x-ray scan is about 0.05 μSv. The unit of a sievert is defined in Chapter 16 of Intermediate Physics for Medicine and Biology as a joule per kilogram (the definition includes a weighting factor for different types of radiation; for x-rays this factor is equal to one). The average annual background dose that we are all exposed to is about 3 mSv, or 3000 μSv, arising mainly from inhalation of the radioactive gas radon. Clearly the dose from a backscatter x-ray scanner is very low, being 60,000 times less than the average yearly background dose.

Nevertheless, the use of x-rays for airport security remains controversial because of our uncertainly about the effect of low doses of radiation. Russ Hobbie and I address this issue in Section 16.13 about the Risk of Radiation.
In dealing with radiation to the population at large, or to populations of radiation workers, the policy of the various regulatory agencies has been to adopt the linear-nonthreshold (LNT) model to extrapolate from what is known about the excess risk of cancer at moderately high doses and high dose rates, to low doses, including those below natural background.

If the excess probability of acquiring a particular disease is αH [where H is the equivalent dose in sieverts] in a population N, the average number of extra persons with the disease is

m = α N H.

The product NH, expressed in person-Sv, is called the collective dose. It is widely used in radiation protection, but it is meaningful only if the LNT assumption is correct [emphasis added].
So, are backscatter x-ray scanners safe? This question was debated in a Point/Counterpoint article appearing in the August issue of Medical Physics, a leading journal published by the American Association of Physicists in Medicine. A Point/Counterpoint article is included in each issue of Medical Physics, providing insight into medical physics topics at a level just right for readers of Intermediate Physics for Medicine and Biology. The format is always the same: two leading medical physicists each defend one side or the other of a controversial proposition. In August, the proposition is “Backscatter X-ray Machines at Airports are Safe.” Elif Hindie of the University of Bordeaux, France argues for the proposition, and David Brenner of Columbia University argues against it.

Now let us see what Drs. Hindie and Brenner have to say about this idea. Hindie writes (references removed)
The LNT model postulates that every dose of radiation, no matter how small, increases the probability of getting cancer. This highly speculative hypothesis was introduced on the basis of flimsy scientific evidence more than 50 years ago, at a time when cellular biology was a largely unexplored field. Over the past decades, an ever-increasing number of scientific studies have consistently shown that the LNT model is incompatible with radiobiological and experimental data, especially for very low doses.

The LNT model was mainly intended as a tool to facilitate radioprotection regulations and, despite its biological implausibility, this may remain its raison d’être. However, the LNT model is now used in a misguided way. Investigators multiply infinitesimal doses by huge numbers of individuals in order to obtain the total number of hypothetical cancers induced in a population. This practice is explicitly condemned as “incorrect” and “not reasonable” by the International Commission on Radiological Protection, among others.
Brenner counters
Of course this individual risk estimate is exceedingly uncertain. Some have argued that the risk at very low doses is zero. Others have argued that phenomena such as tissue/organ microenvironment effects, bystander effects, and “sneaking through” immune surveillance, imply that low-dose radiation risks could be higher than anticipated. The bottom line is that individual risk estimates at very low doses are extremely uncertain.

But when extremely large populations are involved, with up to 109 scans per year in this case, risk should also be viewed from the perspective of the entire exposed population. Population risk quantifies the number of adverse events expected in the exposed population as a result of a proposed practice, and so depends on both the individual risk and on the number of people exposed. Population risk is described by ICRP as “one input to . . . a broad judgment of what is reasonable,” and by NCRP as “one of the means for assessing the acceptability of a facility or practice.” Population risk is considered in many other policy areas where large populations are exposed to very small risks, such as nuclear waste disposal or vaccination.
The debate about the LNT model and the validity of the concept of collective dose is not merely of academic interest. It gets to the heart of how we perceive, assess, and defend ourselves against the risk of radiation. Low doses of radiation are risky to a large population only if there is no threshold below which the risk falls to zero. Until the validity of the linear non-threshold model is confirmed, I suspect we will continue to witness passionate debates—and future point/counterpoint articles—about the safety of ionizing radiation.